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BigFraction.
AbstractUnivariateDifferentiableSolverFieldMatrix methods regardless of the underlying storage.FractionFormat and BigFractionFormat.AbstractIntegerDistribution.AbstractIntegerDistribution(RandomGenerator) instead.
SimpleValueChecker.SimpleValueChecker()
RandomGenerator interface.AbstractRealDistribution.AbstractRealDistribution(RandomGenerator) instead.
SimpleValueChecker.SimpleValueChecker()
StorelessUnivariateStatistic interface.SubHyperplane.UnivariateStatistic interface.Adams-Bashforth and
Adams-Moulton integrators.FunctionUtils.add(UnivariateDifferentiableFunction...)
Complex whose value is
(this + addend).
Complex whose value is (this + addend),
with addend interpreted as a real number.
BigInteger,
returning the result in reduced form.
this and m.
m to this matrix.
this and m.
this and v.
this and v.
v.
this and m.
this and m.
m.
this and m.
this and v.
m.
v.
this and m.
v.
this and v.
Collection of chromosomes to this Population.
data.
ResizableDoubleArray.ExpansionMode.ADDITIVE instead.
this matrix.
this matrix.
this matrix.
this matrix.
this matrix.
this matrix.
SummaryStatistics from several data sets or
data set partitions.(bracketed univariate real) root-finding algorithm may accept as solutions.double[]
arrays.
double[]
arrays.
SummaryStatistics.
Math.FieldElement[][] array to store entries.FieldMatrix<T> with the supplied row and column dimensions.
FieldMatrix<T> using the input array as the underlying
data array.
FieldMatrix<T> using the input array as the underlying
data array.
FieldMatrix<T> using the input array as the underlying
data array.
FieldMatrix<T> using the input array as the underlying
data array.
FieldMatrix<T> using v as the
data for the unique column of the created matrix.
FieldMatrix<T> using v as the
data for the unique column of the created matrix.
RealMatrix using a double[][] array to
store entries.RealMatrix using the input array as the underlying
data array.
v as the
data for the unique column of the created matrix.
FieldVector interface with a FieldElement array.ArrayFieldVector.ArrayFieldVector(FieldVector, FieldVector)
ArrayFieldVector.ArrayFieldVector(FieldVector, FieldElement[])
ArrayFieldVector.ArrayFieldVector(FieldElement[], FieldVector)
RealVector interface with a double array.SimpleValueChecker.SimpleValueChecker()
SimpleValueChecker.SimpleValueChecker()
SimpleVectorValueChecker.SimpleVectorValueChecker()
BigDecimal.
BigDecimal following the passed
rounding mode.
BigDecimal following the passed scale
and rounding mode.
BigFraction equivalent to the passed BigInteger, ie
"num / 1".
BigFraction given the numerator and denominator as
BigInteger.
BigFraction equivalent to the passed int, ie
"num / 1".
BigFraction given the numerator and denominator as simple
int.
BigFraction equivalent to the passed long, ie "num / 1".
BigFraction given the numerator and denominator as simple
long.
FieldMatrix/BigFraction matrix to a RealMatrix.
BinaryChromosomes.n choose k", the number of
k-element subsets that can be selected from an
n-element set.
double representation of the Binomial
Coefficient, "n choose k", the number of
k-element subsets that can be selected from an
n-element set.
log of the Binomial
Coefficient, "n choose k", the number of
k-element subsets that can be selected from an
n-element set.
lowerBound <= a < initial < b <= upperBound
f(a) * f(b) < 0
If f is continuous on [a,b], this means that a
and b bracket a root of f.
lowerBound <= a < initial < b <= upperBound
f(a) * f(b) <= 0
If f is continuous on [a,b], this means that a
and b bracket a root of f.
(univariate real) root-finding
algorithms that maintain a bracketed solution.100, 50 (see the
other constructor).
100, 50 (see the
other constructor).
(lo, hi), this class
finds an approximation x to the point at which the function
attains its minimum.BSP tree nodes.MathArrays.buildArray(Field, int, int)
MathArrays.buildArray(Field, int)
byte.
sum of squared residuals,
SSTO is the total sum of squares, n is the number
of observations and p is the number of parameters estimated (including the intercept).
WeibullDistribution.getNumericalMean()
ZipfDistribution.getNumericalMean().
FDistribution.getNumericalVariance()
HypergeometricDistribution.getNumericalVariance().
WeibullDistribution.getNumericalVariance()
ZipfDistribution.getNumericalVariance().
sum of squared residuals
and SSTO is the total sum of squares
P(D_n < d) using method described in [1] with quick
decisions for extreme values given in [2] (see above).
P(D_n < d) using method described in [1] with quick
decisions for extreme values given in [2] (see above).
P(D_n < d) using method described in [1] with quick
decisions for extreme values given in [2] (see above).
ceil function.ResizableDoubleArray.checkContractExpand(double,double) instead.
solve and
solveInPlace,
and throws an exception if one of the checks fails.
solve
and
solveInPlace,
and throws an exception if one of the checks fails.
representation can represent a valid chromosome.
representation can represent a valid chromosome.
representation can represent a valid chromosome.
observed and expected
frequency counts.
counts
array, viewed as a two-way table.
observed1 and observed2.
observed
frequency counts to those in the expected array.
alpha.
counts
array, viewed as a two-way table.
alpha.
observed1 and
observed2.
Chromosome objects.AbstractRandomGenerator.nextGaussian().
BitsStreamGenerator.nextGaussian.
valuesFileURL after use in REPLAY_MODE.
Clusterable points.Clusterable instances.
Cluster insteadClusterable insteadDistanceMeasure.
lambda must be
passed with the call to optimize (whereas in the current code it is set to an undocumented value).
lambda must be
passed with the call to optimize (whereas in the current code it is set to an undocumented value)..
lambda and inputSigma must be
passed with the call to optimize.
SimpleValueChecker.SimpleValueChecker()
lambda and inputSigma must be
passed with the call to optimize.
h(x[]) = combiner(...combiner(combiner(initialValue,f(x[0])),f(x[1]))...)
- collector(BivariateFunction, double) -
Static method in class org.apache.commons.math3.analysis.FunctionUtils
- Returns a MultivariateFunction h(x[]) defined by
h(x[]) = combiner(...combiner(combiner(initialValue,x[0]),x[1])...)
- cols -
Variable in class org.apache.commons.math3.optimization.general.AbstractLeastSquaresOptimizer
- Deprecated. As of 3.1.
- combine(BivariateFunction, UnivariateFunction, UnivariateFunction) -
Static method in class org.apache.commons.math3.analysis.FunctionUtils
- Returns the univariate function
h(x) = combiner(f(x), g(x)).
- combine(double, double, RealVector) -
Method in class org.apache.commons.math3.linear.ArrayRealVector
- Returns a new vector representing
a * this + b * y, the linear
combination of this and y.
- combine(double, double, RealVector) -
Method in class org.apache.commons.math3.linear.RealVector
- Returns a new vector representing
a * this + b * y, the linear
combination of this and y.
- combineToSelf(double, double, RealVector) -
Method in class org.apache.commons.math3.linear.ArrayRealVector
- Updates
this with the linear combination of this and
y.
- combineToSelf(double, double, RealVector) -
Method in class org.apache.commons.math3.linear.RealVector
- Updates
this with the linear combination of this and
y.
- comparatorPermutation(List<S>, Comparator<S>) -
Static method in class org.apache.commons.math3.genetics.RandomKey
- Generates a representation of a permutation corresponding to the
data sorted by comparator.
- compareTo(BigFraction) -
Method in class org.apache.commons.math3.fraction.BigFraction
-
Compares this object to another based on size.
- compareTo(Fraction) -
Method in class org.apache.commons.math3.fraction.Fraction
- Compares this object to another based on size.
- compareTo(Chromosome) -
Method in class org.apache.commons.math3.genetics.Chromosome
- Compares two chromosomes based on their fitness.
- compareTo(OrderedTuple) -
Method in class org.apache.commons.math3.geometry.partitioning.utilities.OrderedTuple
- Compares this ordered T-uple with the specified object.
- compareTo(BigReal) -
Method in class org.apache.commons.math3.util.BigReal
-
- compareTo(Decimal64) -
Method in class org.apache.commons.math3.util.Decimal64
-
The current implementation returns the same value as
new Double(this.doubleValue()).compareTo(new
Double(o.doubleValue()))
- compareTo(double, double, double) -
Static method in class org.apache.commons.math3.util.Precision
- Compares two numbers given some amount of allowed error.
- compareTo(double, double, int) -
Static method in class org.apache.commons.math3.util.Precision
- Compares two numbers given some amount of allowed error.
- complainIfNotSupported(String) -
Method in class org.apache.commons.math3.ode.AbstractParameterizable
- Check if a parameter is supported and throw an IllegalArgumentException if not.
- complement(int) -
Method in class org.apache.commons.math3.dfp.Dfp
- Negate the mantissa of this by computing the complement.
- Complex - Class in org.apache.commons.math3.complex
- Representation of a Complex number, i.e. a number which has both a
real and imaginary part.
- Complex(double) -
Constructor for class org.apache.commons.math3.complex.Complex
- Create a complex number given only the real part.
- Complex(double, double) -
Constructor for class org.apache.commons.math3.complex.Complex
- Create a complex number given the real and imaginary parts.
- ComplexField - Class in org.apache.commons.math3.complex
- Representation of the complex numbers field.
- ComplexFormat - Class in org.apache.commons.math3.complex
- Formats a Complex number in cartesian format "Re(c) + Im(c)i".
- ComplexFormat() -
Constructor for class org.apache.commons.math3.complex.ComplexFormat
- Create an instance with the default imaginary character, 'i', and the
default number format for both real and imaginary parts.
- ComplexFormat(NumberFormat) -
Constructor for class org.apache.commons.math3.complex.ComplexFormat
- Create an instance with a custom number format for both real and
imaginary parts.
- ComplexFormat(NumberFormat, NumberFormat) -
Constructor for class org.apache.commons.math3.complex.ComplexFormat
- Create an instance with a custom number format for the real part and a
custom number format for the imaginary part.
- ComplexFormat(String) -
Constructor for class org.apache.commons.math3.complex.ComplexFormat
- Create an instance with a custom imaginary character, and the default
number format for both real and imaginary parts.
- ComplexFormat(String, NumberFormat) -
Constructor for class org.apache.commons.math3.complex.ComplexFormat
- Create an instance with a custom imaginary character, and a custom number
format for both real and imaginary parts.
- ComplexFormat(String, NumberFormat, NumberFormat) -
Constructor for class org.apache.commons.math3.complex.ComplexFormat
- Create an instance with a custom imaginary character, a custom number
format for the real part, and a custom number format for the imaginary
part.
- ComplexUtils - Class in org.apache.commons.math3.complex
- Static implementations of common
Complex utilities functions. - compose(double...) -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- Compute composition of the instance by a univariate function.
- compose(double[], int, double[], double[], int) -
Method in class org.apache.commons.math3.analysis.differentiation.DSCompiler
- Compute composition of a derivative structure by a function.
- compose(UnivariateFunction...) -
Static method in class org.apache.commons.math3.analysis.FunctionUtils
- Composes functions.
- compose(UnivariateDifferentiableFunction...) -
Static method in class org.apache.commons.math3.analysis.FunctionUtils
- Composes functions.
- compose(DifferentiableUnivariateFunction...) -
Static method in class org.apache.commons.math3.analysis.FunctionUtils
- Deprecated. as of 3.1 replaced by
FunctionUtils.compose(UnivariateDifferentiableFunction...)
- CompositeFormat - Class in org.apache.commons.math3.util
- Base class for formatters of composite objects (complex numbers, vectors ...).
- compute(double[], double[]) -
Method in class org.apache.commons.math3.ml.distance.CanberraDistance
- Compute the distance between two n-dimensional vectors.
- compute(double[], double[]) -
Method in class org.apache.commons.math3.ml.distance.ChebyshevDistance
- Compute the distance between two n-dimensional vectors.
- compute(double[], double[]) -
Method in interface org.apache.commons.math3.ml.distance.DistanceMeasure
- Compute the distance between two n-dimensional vectors.
- compute(double[], double[]) -
Method in class org.apache.commons.math3.ml.distance.EuclideanDistance
- Compute the distance between two n-dimensional vectors.
- compute(double[], double[]) -
Method in class org.apache.commons.math3.ml.distance.ManhattanDistance
- Compute the distance between two n-dimensional vectors.
- compute(MathArrays.Function) -
Method in class org.apache.commons.math3.util.ResizableDoubleArray
- Performs an operation on the addressable elements of the array.
- computeCoefficients() -
Method in class org.apache.commons.math3.analysis.polynomials.PolynomialFunctionLagrangeForm
- Calculate the coefficients of Lagrange polynomial from the
interpolation data.
- computeCoefficients() -
Method in class org.apache.commons.math3.analysis.polynomials.PolynomialFunctionNewtonForm
- Calculate the normal polynomial coefficients given the Newton form.
- computeCorrelationMatrix(RealMatrix) -
Method in class org.apache.commons.math3.stat.correlation.PearsonsCorrelation
- Computes the correlation matrix for the columns of the
input matrix.
- computeCorrelationMatrix(double[][]) -
Method in class org.apache.commons.math3.stat.correlation.PearsonsCorrelation
- Computes the correlation matrix for the columns of the
input rectangular array.
- computeCorrelationMatrix(RealMatrix) -
Method in class org.apache.commons.math3.stat.correlation.SpearmansCorrelation
- Computes the Spearman's rank correlation matrix for the columns of the
input matrix.
- computeCorrelationMatrix(double[][]) -
Method in class org.apache.commons.math3.stat.correlation.SpearmansCorrelation
- Computes the Spearman's rank correlation matrix for the columns of the
input rectangular array.
- computeCost(double[]) -
Method in class org.apache.commons.math3.optim.nonlinear.vector.jacobian.AbstractLeastSquaresOptimizer
- Computes the cost.
- computeCost(double[]) -
Method in class org.apache.commons.math3.optimization.general.AbstractLeastSquaresOptimizer
- Deprecated. Computes the cost.
- computeCovarianceMatrix(RealMatrix, boolean) -
Method in class org.apache.commons.math3.stat.correlation.Covariance
- Compute a covariance matrix from a matrix whose columns represent
covariates.
- computeCovarianceMatrix(RealMatrix) -
Method in class org.apache.commons.math3.stat.correlation.Covariance
- Create a covariance matrix from a matrix whose columns represent
covariates.
- computeCovarianceMatrix(double[][], boolean) -
Method in class org.apache.commons.math3.stat.correlation.Covariance
- Compute a covariance matrix from a rectangular array whose columns represent
covariates.
- computeCovarianceMatrix(double[][]) -
Method in class org.apache.commons.math3.stat.correlation.Covariance
- Create a covariance matrix from a rectangular array whose columns represent
covariates.
- computeCovariances(double[], double) -
Method in class org.apache.commons.math3.optim.nonlinear.vector.jacobian.AbstractLeastSquaresOptimizer
- Get the covariance matrix of the optimized parameters.
- computeCovariances(double[], double) -
Method in class org.apache.commons.math3.optimization.general.AbstractLeastSquaresOptimizer
- Deprecated. Get the covariance matrix of the optimized parameters.
- computeDerivativeObjectiveValue(double) -
Method in class org.apache.commons.math3.analysis.solvers.AbstractDifferentiableUnivariateSolver
- Deprecated. Compute the objective function value.
- computeDerivatives(double, double[], double[]) -
Method in class org.apache.commons.math3.ode.AbstractIntegrator
- Compute the derivatives and check the number of evaluations.
- computeDerivatives(double, double[], double[]) -
Method in class org.apache.commons.math3.ode.ExpandableStatefulODE
- Get the current time derivative of the complete state vector.
- computeDerivatives(double, double[], double[]) -
Method in class org.apache.commons.math3.ode.FirstOrderConverter
- Get the current time derivative of the state vector.
- computeDerivatives(double, double[], double[]) -
Method in interface org.apache.commons.math3.ode.FirstOrderDifferentialEquations
- Get the current time derivative of the state vector.
- computeDerivatives(double, double[], double[], double[], double[]) -
Method in interface org.apache.commons.math3.ode.SecondaryEquations
- Compute the derivatives related to the secondary state parameters.
- computeDistribution() -
Method in class org.apache.commons.math3.random.ValueServer
- Computes the empirical distribution using values from the file
in
valuesFileURL, using the default number of bins.
- computeDistribution(int) -
Method in class org.apache.commons.math3.random.ValueServer
- Computes the empirical distribution using values from the file
in
valuesFileURL and binCount bins.
- computeDividedDifference(double[], double[]) -
Static method in class org.apache.commons.math3.analysis.interpolation.DividedDifferenceInterpolator
- Return a copy of the divided difference array.
- computeExp(Dfp, Dfp) -
Static method in class org.apache.commons.math3.dfp.DfpField
- Compute exp(a).
- computeGeometricalProperties() -
Method in class org.apache.commons.math3.geometry.euclidean.oned.IntervalsSet
- Compute some geometrical properties.
- computeGeometricalProperties() -
Method in class org.apache.commons.math3.geometry.euclidean.threed.PolyhedronsSet
- Compute some geometrical properties.
- computeGeometricalProperties() -
Method in class org.apache.commons.math3.geometry.euclidean.twod.PolygonsSet
- Compute some geometrical properties.
- computeGeometricalProperties() -
Method in class org.apache.commons.math3.geometry.partitioning.AbstractRegion
- Compute some geometrical properties.
- computeInterpolatedStateAndDerivatives(double, double) -
Method in class org.apache.commons.math3.ode.sampling.AbstractStepInterpolator
- Compute the state and derivatives at the interpolated time.
- computeInterpolatedStateAndDerivatives(double, double) -
Method in class org.apache.commons.math3.ode.sampling.NordsieckStepInterpolator
- Compute the state and derivatives at the interpolated time.
- computeJacobian(double[]) -
Method in class org.apache.commons.math3.optim.nonlinear.vector.JacobianMultivariateVectorOptimizer
- Computes the Jacobian matrix.
- computeLn(Dfp, Dfp, Dfp) -
Static method in class org.apache.commons.math3.dfp.DfpField
- Compute ln(a).
- computeMainStateJacobian(double, double[], double[], double[][]) -
Method in interface org.apache.commons.math3.ode.MainStateJacobianProvider
- Compute the jacobian matrix of ODE with respect to main state.
- computeObjectiveGradient(double[]) -
Method in class org.apache.commons.math3.optim.nonlinear.scalar.GradientMultivariateOptimizer
- Compute the gradient vector.
- computeObjectiveGradient(double[]) -
Method in class org.apache.commons.math3.optimization.general.AbstractDifferentiableOptimizer
- Deprecated. Compute the gradient vector.
- computeObjectiveGradient(double[]) -
Method in class org.apache.commons.math3.optimization.general.AbstractScalarDifferentiableOptimizer
- Deprecated. Compute the gradient vector.
- computeObjectiveValue(double) -
Method in class org.apache.commons.math3.analysis.integration.BaseAbstractUnivariateIntegrator
- Compute the objective function value.
- computeObjectiveValue(double) -
Method in class org.apache.commons.math3.analysis.solvers.BaseAbstractUnivariateSolver
- Compute the objective function value.
- computeObjectiveValue(double[]) -
Method in class org.apache.commons.math3.optim.nonlinear.scalar.MultivariateOptimizer
- Computes the objective function value.
- computeObjectiveValue(double[]) -
Method in class org.apache.commons.math3.optim.nonlinear.vector.MultivariateVectorOptimizer
- Computes the objective function value.
- computeObjectiveValue(double) -
Method in class org.apache.commons.math3.optim.univariate.UnivariateOptimizer
- Computes the objective function value.
- computeObjectiveValue(double[]) -
Method in class org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateOptimizer
- Deprecated. Compute the objective function value.
- computeObjectiveValue(double[]) -
Method in class org.apache.commons.math3.optimization.direct.BaseAbstractMultivariateVectorOptimizer
- Deprecated. Compute the objective function value.
- computeObjectiveValue(double) -
Method in class org.apache.commons.math3.optimization.univariate.BaseAbstractUnivariateOptimizer
- Deprecated. Compute the objective function value.
- computeObjectiveValueAndDerivative(double) -
Method in class org.apache.commons.math3.analysis.solvers.AbstractUnivariateDifferentiableSolver
- Compute the objective function value.
- computeParameterJacobian(double, double[], double[], String, double[]) -
Method in interface org.apache.commons.math3.ode.ParameterJacobianProvider
- Compute the Jacobian matrix of ODE with respect to one parameter.
- computeResiduals(double[]) -
Method in class org.apache.commons.math3.optim.nonlinear.vector.jacobian.AbstractLeastSquaresOptimizer
- Computes the residuals.
- computeResiduals(double[]) -
Method in class org.apache.commons.math3.optimization.general.AbstractLeastSquaresOptimizer
- Deprecated. Computes the residuals.
- computeRoots(int) -
Method in class org.apache.commons.math3.complex.RootsOfUnity
-
Computes the
n-th roots of unity.
- computeRule(int) -
Method in class org.apache.commons.math3.analysis.integration.gauss.BaseRuleFactory
- Computes the rule for the given order.
- computeRule(int) -
Method in class org.apache.commons.math3.analysis.integration.gauss.LegendreHighPrecisionRuleFactory
- Computes the rule for the given order.
- computeRule(int) -
Method in class org.apache.commons.math3.analysis.integration.gauss.LegendreRuleFactory
- Computes the rule for the given order.
- computeSecondDerivatives(double, double[], double[], double[]) -
Method in interface org.apache.commons.math3.ode.SecondOrderDifferentialEquations
- Get the current time derivative of the state vector.
- computeSigma(double[], double) -
Method in class org.apache.commons.math3.optim.nonlinear.vector.jacobian.AbstractLeastSquaresOptimizer
- Computes an estimate of the standard deviation of the parameters.
- computeSigma(double[], double) -
Method in class org.apache.commons.math3.optimization.general.AbstractLeastSquaresOptimizer
- Deprecated. Computes an estimate of the standard deviation of the parameters.
- computeStepGrowShrinkFactor(double) -
Method in class org.apache.commons.math3.ode.MultistepIntegrator
- Compute step grow/shrink factor according to normalized error.
- computeWeightedJacobian(double[]) -
Method in class org.apache.commons.math3.optim.nonlinear.vector.jacobian.AbstractLeastSquaresOptimizer
- Computes the weighted Jacobian matrix.
- computeWeightedJacobian(double[]) -
Method in class org.apache.commons.math3.optimization.general.AbstractLeastSquaresOptimizer
- Deprecated. Computes the Jacobian matrix.
- conjugate() -
Method in class org.apache.commons.math3.complex.Complex
- Return the conjugate of this complex number.
- ConjugateGradient - Class in org.apache.commons.math3.linear
-
This is an implementation of the conjugate gradient method for
RealLinearOperator. - ConjugateGradient(int, double, boolean) -
Constructor for class org.apache.commons.math3.linear.ConjugateGradient
- Creates a new instance of this class, with default
stopping criterion.
- ConjugateGradient(IterationManager, double, boolean) -
Constructor for class org.apache.commons.math3.linear.ConjugateGradient
- Creates a new instance of this class, with default
stopping criterion and custom iteration manager.
- ConjugateGradientFormula - Enum in org.apache.commons.math3.optimization.general
- Deprecated. As of 3.1 (to be removed in 4.0).
- Constant - Class in org.apache.commons.math3.analysis.function
- Constant function.
- Constant(double) -
Constructor for class org.apache.commons.math3.analysis.function.Constant
-
- CONSTANT_MODE -
Static variable in class org.apache.commons.math3.random.ValueServer
- Always return mu
- contains(Vector3D) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.Line
- Check if the instance contains a point.
- contains(Vector3D) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.Plane
- Check if the instance contains a point.
- contains(Vector2D) -
Method in class org.apache.commons.math3.geometry.euclidean.twod.Line
- Check if the line contains a point.
- contains(Region<S>) -
Method in class org.apache.commons.math3.geometry.partitioning.AbstractRegion
- Check if the instance entirely contains another region.
- contains(Region<S>) -
Method in interface org.apache.commons.math3.geometry.partitioning.Region
- Check if the instance entirely contains another region.
- containsClass(Class<?>) -
Method in class org.apache.commons.math3.util.TransformerMap
- Tests if a Class is present in the TransformerMap.
- containsKey(int) -
Method in class org.apache.commons.math3.util.OpenIntToDoubleHashMap
- Check if a value is associated with a key.
- containsKey(int) -
Method in class org.apache.commons.math3.util.OpenIntToFieldHashMap
- Check if a value is associated with a key.
- containsTransformer(NumberTransformer) -
Method in class org.apache.commons.math3.util.TransformerMap
- Tests if a NumberTransformer is present in the TransformerMap.
- ContinuedFraction - Class in org.apache.commons.math3.util
- Provides a generic means to evaluate continued fractions.
- ContinuedFraction() -
Constructor for class org.apache.commons.math3.util.ContinuedFraction
- Default constructor.
- ContinuousOutputModel - Class in org.apache.commons.math3.ode
- This class stores all information provided by an ODE integrator
during the integration process and build a continuous model of the
solution from this.
- ContinuousOutputModel() -
Constructor for class org.apache.commons.math3.ode.ContinuousOutputModel
- Simple constructor.
- contract() -
Method in class org.apache.commons.math3.util.ResizableDoubleArray
- Contracts the storage array to the (size of the element set) + 1 - to
avoid a zero length array.
- converged(int, PAIR, PAIR) -
Method in class org.apache.commons.math3.optim.AbstractConvergenceChecker
- Check if the optimization algorithm has converged.
- converged(int, PAIR, PAIR) -
Method in interface org.apache.commons.math3.optim.ConvergenceChecker
- Check if the optimization algorithm has converged.
- converged(int, PAIR, PAIR) -
Method in class org.apache.commons.math3.optim.SimplePointChecker
- Check if the optimization algorithm has converged considering the
last two points.
- converged(int, PointValuePair, PointValuePair) -
Method in class org.apache.commons.math3.optim.SimpleValueChecker
- Check if the optimization algorithm has converged considering the
last two points.
- converged(int, PointVectorValuePair, PointVectorValuePair) -
Method in class org.apache.commons.math3.optim.SimpleVectorValueChecker
- Check if the optimization algorithm has converged considering the
last two points.
- converged(int, UnivariatePointValuePair, UnivariatePointValuePair) -
Method in class org.apache.commons.math3.optim.univariate.SimpleUnivariateValueChecker
- Check if the optimization algorithm has converged considering the
last two points.
- converged(int, PAIR, PAIR) -
Method in class org.apache.commons.math3.optimization.AbstractConvergenceChecker
- Deprecated. Check if the optimization algorithm has converged.
- converged(int, PAIR, PAIR) -
Method in interface org.apache.commons.math3.optimization.ConvergenceChecker
- Deprecated. Check if the optimization algorithm has converged.
- converged(int, PAIR, PAIR) -
Method in class org.apache.commons.math3.optimization.SimplePointChecker
- Deprecated. Check if the optimization algorithm has converged considering the
last two points.
- converged(int, PointValuePair, PointValuePair) -
Method in class org.apache.commons.math3.optimization.SimpleValueChecker
- Deprecated. Check if the optimization algorithm has converged considering the
last two points.
- converged(int, PointVectorValuePair, PointVectorValuePair) -
Method in class org.apache.commons.math3.optimization.SimpleVectorValueChecker
- Deprecated. Check if the optimization algorithm has converged considering the
last two points.
- converged(int, UnivariatePointValuePair, UnivariatePointValuePair) -
Method in class org.apache.commons.math3.optimization.univariate.SimpleUnivariateValueChecker
- Deprecated. Check if the optimization algorithm has converged considering the
last two points.
- ConvergenceChecker<PAIR> - Interface in org.apache.commons.math3.optim
- This interface specifies how to check if an optimization algorithm has
converged.
- ConvergenceChecker<PAIR> - Interface in org.apache.commons.math3.optimization
- Deprecated. As of 3.1 (to be removed in 4.0).
- ConvergenceException - Exception in org.apache.commons.math3.exception
- Error thrown when a numerical computation can not be performed because the
numerical result failed to converge to a finite value.
- ConvergenceException() -
Constructor for exception org.apache.commons.math3.exception.ConvergenceException
- Construct the exception.
- ConvergenceException(Localizable, Object...) -
Constructor for exception org.apache.commons.math3.exception.ConvergenceException
- Construct the exception with a specific context and arguments.
- convertToComplex(double[]) -
Static method in class org.apache.commons.math3.complex.ComplexUtils
- Convert an array of primitive doubles to an array of
Complex objects.
- copy() -
Method in class org.apache.commons.math3.linear.AbstractFieldMatrix
- Make a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.AbstractRealMatrix
- Returns a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.Array2DRowFieldMatrix
- Make a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.Array2DRowRealMatrix
- Returns a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.ArrayFieldVector
- Returns a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.ArrayRealVector
- Returns a (deep) copy of this vector.
- copy() -
Method in class org.apache.commons.math3.linear.BlockFieldMatrix
- Make a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.BlockRealMatrix
- Returns a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.DiagonalMatrix
- Returns a (deep) copy of this.
- copy() -
Method in interface org.apache.commons.math3.linear.FieldMatrix
- Make a (deep) copy of this.
- copy() -
Method in interface org.apache.commons.math3.linear.FieldVector
- Returns a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.OpenMapRealMatrix
- Deprecated. Returns a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.OpenMapRealVector
- Deprecated. Returns a (deep) copy of this vector.
- copy() -
Method in interface org.apache.commons.math3.linear.RealMatrix
- Returns a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.RealVector
- Returns a (deep) copy of this vector.
- copy() -
Method in class org.apache.commons.math3.linear.SparseFieldMatrix
- Deprecated. Make a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.linear.SparseFieldVector
- Deprecated. Returns a (deep) copy of this.
- copy() -
Method in class org.apache.commons.math3.ode.sampling.AbstractStepInterpolator
- Copy the instance.
- copy() -
Method in interface org.apache.commons.math3.ode.sampling.StepInterpolator
- Copy the instance.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.AbstractStorelessUnivariateStatistic
- Returns a copy of the statistic with the same internal state.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.AbstractUnivariateStatistic
- Returns a copy of the statistic with the same internal state.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.DescriptiveStatistics
- Returns a copy of this DescriptiveStatistics instance with the same internal state.
- copy(DescriptiveStatistics, DescriptiveStatistics) -
Static method in class org.apache.commons.math3.stat.descriptive.DescriptiveStatistics
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.moment.GeometricMean
- Returns a copy of the statistic with the same internal state.
- copy(GeometricMean, GeometricMean) -
Static method in class org.apache.commons.math3.stat.descriptive.moment.GeometricMean
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.moment.Kurtosis
- Returns a copy of the statistic with the same internal state.
- copy(Kurtosis, Kurtosis) -
Static method in class org.apache.commons.math3.stat.descriptive.moment.Kurtosis
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.moment.Mean
- Returns a copy of the statistic with the same internal state.
- copy(Mean, Mean) -
Static method in class org.apache.commons.math3.stat.descriptive.moment.Mean
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.moment.SecondMoment
- Returns a copy of the statistic with the same internal state.
- copy(SecondMoment, SecondMoment) -
Static method in class org.apache.commons.math3.stat.descriptive.moment.SecondMoment
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.moment.SemiVariance
- Returns a copy of the statistic with the same internal state.
- copy(SemiVariance, SemiVariance) -
Static method in class org.apache.commons.math3.stat.descriptive.moment.SemiVariance
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.moment.Skewness
- Returns a copy of the statistic with the same internal state.
- copy(Skewness, Skewness) -
Static method in class org.apache.commons.math3.stat.descriptive.moment.Skewness
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.moment.StandardDeviation
- Returns a copy of the statistic with the same internal state.
- copy(StandardDeviation, StandardDeviation) -
Static method in class org.apache.commons.math3.stat.descriptive.moment.StandardDeviation
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.moment.Variance
- Returns a copy of the statistic with the same internal state.
- copy(Variance, Variance) -
Static method in class org.apache.commons.math3.stat.descriptive.moment.Variance
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.rank.Max
- Returns a copy of the statistic with the same internal state.
- copy(Max, Max) -
Static method in class org.apache.commons.math3.stat.descriptive.rank.Max
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.rank.Min
- Returns a copy of the statistic with the same internal state.
- copy(Min, Min) -
Static method in class org.apache.commons.math3.stat.descriptive.rank.Min
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.rank.Percentile
- Returns a copy of the statistic with the same internal state.
- copy(Percentile, Percentile) -
Static method in class org.apache.commons.math3.stat.descriptive.rank.Percentile
- Copies source to dest.
- copy() -
Method in interface org.apache.commons.math3.stat.descriptive.StorelessUnivariateStatistic
- Returns a copy of the statistic with the same internal state.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.summary.Product
- Returns a copy of the statistic with the same internal state.
- copy(Product, Product) -
Static method in class org.apache.commons.math3.stat.descriptive.summary.Product
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.summary.Sum
- Returns a copy of the statistic with the same internal state.
- copy(Sum, Sum) -
Static method in class org.apache.commons.math3.stat.descriptive.summary.Sum
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.summary.SumOfLogs
- Returns a copy of the statistic with the same internal state.
- copy(SumOfLogs, SumOfLogs) -
Static method in class org.apache.commons.math3.stat.descriptive.summary.SumOfLogs
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.summary.SumOfSquares
- Returns a copy of the statistic with the same internal state.
- copy(SumOfSquares, SumOfSquares) -
Static method in class org.apache.commons.math3.stat.descriptive.summary.SumOfSquares
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.SummaryStatistics
- Returns a copy of this SummaryStatistics instance with the same internal state.
- copy(SummaryStatistics, SummaryStatistics) -
Static method in class org.apache.commons.math3.stat.descriptive.SummaryStatistics
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.SynchronizedDescriptiveStatistics
- Returns a copy of this SynchronizedDescriptiveStatistics instance with the
same internal state.
- copy(SynchronizedDescriptiveStatistics, SynchronizedDescriptiveStatistics) -
Static method in class org.apache.commons.math3.stat.descriptive.SynchronizedDescriptiveStatistics
- Copies source to dest.
- copy() -
Method in class org.apache.commons.math3.stat.descriptive.SynchronizedSummaryStatistics
- Returns a copy of this SynchronizedSummaryStatistics instance with the
same internal state.
- copy(SynchronizedSummaryStatistics, SynchronizedSummaryStatistics) -
Static method in class org.apache.commons.math3.stat.descriptive.SynchronizedSummaryStatistics
- Copies source to dest.
- copy() -
Method in interface org.apache.commons.math3.stat.descriptive.UnivariateStatistic
- Returns a copy of the statistic with the same internal state.
- copy(ResizableDoubleArray, ResizableDoubleArray) -
Static method in class org.apache.commons.math3.util.ResizableDoubleArray
- Copies source to dest, copying the underlying data, so dest is
a new, independent copy of source.
- copy() -
Method in class org.apache.commons.math3.util.ResizableDoubleArray
- Returns a copy of the ResizableDoubleArray.
- copyOf(int[]) -
Static method in class org.apache.commons.math3.util.MathArrays
- Creates a copy of the
source array.
- copyOf(double[]) -
Static method in class org.apache.commons.math3.util.MathArrays
- Creates a copy of the
source array.
- copyOf(int[], int) -
Static method in class org.apache.commons.math3.util.MathArrays
- Creates a copy of the
source array.
- copyOf(double[], int) -
Static method in class org.apache.commons.math3.util.MathArrays
- Creates a copy of the
source array.
- copySelf() -
Method in class org.apache.commons.math3.geometry.euclidean.oned.OrientedPoint
- Copy the instance.
- copySelf() -
Method in class org.apache.commons.math3.geometry.euclidean.threed.Plane
- Copy the instance.
- copySelf() -
Method in class org.apache.commons.math3.geometry.euclidean.twod.Line
- Copy the instance.
- copySelf() -
Method in class org.apache.commons.math3.geometry.partitioning.AbstractRegion
- Copy the instance.
- copySelf() -
Method in class org.apache.commons.math3.geometry.partitioning.AbstractSubHyperplane
- Copy the instance.
- copySelf() -
Method in class org.apache.commons.math3.geometry.partitioning.BSPTree
- Copy the instance.
- copySelf() -
Method in interface org.apache.commons.math3.geometry.partitioning.Hyperplane
- Copy the instance.
- copySelf() -
Method in interface org.apache.commons.math3.geometry.partitioning.Region
- Copy the instance.
- copySelf() -
Method in interface org.apache.commons.math3.geometry.partitioning.SubHyperplane
- Copy the instance.
- copySign(DerivativeStructure) -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- Returns the instance with the sign of the argument.
- copySign(double) -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- Returns the instance with the sign of the argument.
- copysign(Dfp, Dfp) -
Static method in class org.apache.commons.math3.dfp.Dfp
- Creates an instance that is the same as x except that it has the sign of y.
- copySign(Dfp) -
Method in class org.apache.commons.math3.dfp.Dfp
- Returns the instance with the sign of the argument.
- copySign(double) -
Method in class org.apache.commons.math3.dfp.Dfp
- Returns the instance with the sign of the argument.
- copySign(T) -
Method in interface org.apache.commons.math3.RealFieldElement
- Returns the instance with the sign of the argument.
- copySign(double) -
Method in interface org.apache.commons.math3.RealFieldElement
- Returns the instance with the sign of the argument.
- copySign(Decimal64) -
Method in class org.apache.commons.math3.util.Decimal64
- Returns the instance with the sign of the argument.
- copySign(double) -
Method in class org.apache.commons.math3.util.Decimal64
- Returns the instance with the sign of the argument.
- copySign(double, double) -
Static method in class org.apache.commons.math3.util.FastMath
- Returns the first argument with the sign of the second argument.
- copySign(float, float) -
Static method in class org.apache.commons.math3.util.FastMath
- Returns the first argument with the sign of the second argument.
- copySign(byte, byte) -
Static method in class org.apache.commons.math3.util.MathUtils
- Returns the first argument with the sign of the second argument.
- copySign(short, short) -
Static method in class org.apache.commons.math3.util.MathUtils
- Returns the first argument with the sign of the second argument.
- copySign(int, int) -
Static method in class org.apache.commons.math3.util.MathUtils
- Returns the first argument with the sign of the second argument.
- copySign(long, long) -
Static method in class org.apache.commons.math3.util.MathUtils
- Returns the first argument with the sign of the second argument.
- copySubMatrix(int, int, int, int, T[][]) -
Method in class org.apache.commons.math3.linear.AbstractFieldMatrix
- Copy a submatrix.
- copySubMatrix(int[], int[], T[][]) -
Method in class org.apache.commons.math3.linear.AbstractFieldMatrix
- Copy a submatrix.
- copySubMatrix(int, int, int, int, double[][]) -
Method in class org.apache.commons.math3.linear.AbstractRealMatrix
- Copy a submatrix.
- copySubMatrix(int[], int[], double[][]) -
Method in class org.apache.commons.math3.linear.AbstractRealMatrix
- Copy a submatrix.
- copySubMatrix(int, int, int, int, T[][]) -
Method in interface org.apache.commons.math3.linear.FieldMatrix
- Copy a submatrix.
- copySubMatrix(int[], int[], T[][]) -
Method in interface org.apache.commons.math3.linear.FieldMatrix
- Copy a submatrix.
- copySubMatrix(int, int, int, int, double[][]) -
Method in interface org.apache.commons.math3.linear.RealMatrix
- Copy a submatrix.
- copySubMatrix(int[], int[], double[][]) -
Method in interface org.apache.commons.math3.linear.RealMatrix
- Copy a submatrix.
- correct(double[]) -
Method in class org.apache.commons.math3.filter.KalmanFilter
- Correct the current state estimate with an actual measurement.
- correct(RealVector) -
Method in class org.apache.commons.math3.filter.KalmanFilter
- Correct the current state estimate with an actual measurement.
- CorrelatedRandomVectorGenerator - Class in org.apache.commons.math3.random
- A
RandomVectorGenerator that generates vectors with with
correlated components. - CorrelatedRandomVectorGenerator(double[], RealMatrix, double, NormalizedRandomGenerator) -
Constructor for class org.apache.commons.math3.random.CorrelatedRandomVectorGenerator
- Builds a correlated random vector generator from its mean
vector and covariance matrix.
- CorrelatedRandomVectorGenerator(RealMatrix, double, NormalizedRandomGenerator) -
Constructor for class org.apache.commons.math3.random.CorrelatedRandomVectorGenerator
- Builds a null mean random correlated vector generator from its
covariance matrix.
- correlation(double[], double[]) -
Method in class org.apache.commons.math3.stat.correlation.PearsonsCorrelation
- Computes the Pearson's product-moment correlation coefficient between the two arrays.
- correlation(double[], double[]) -
Method in class org.apache.commons.math3.stat.correlation.SpearmansCorrelation
- Computes the Spearman's rank correlation coefficient between the two arrays.
- cos() -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- Cosine operation.
- cos(double[], int, double[], int) -
Method in class org.apache.commons.math3.analysis.differentiation.DSCompiler
- Compute cosine of a derivative structure.
- Cos - Class in org.apache.commons.math3.analysis.function
- Cosine function.
- Cos() -
Constructor for class org.apache.commons.math3.analysis.function.Cos
-
- cos() -
Method in class org.apache.commons.math3.complex.Complex
- Compute the
cosine
of this complex number.
- cos() -
Method in class org.apache.commons.math3.dfp.Dfp
- Cosine operation.
- cos(Dfp) -
Static method in class org.apache.commons.math3.dfp.DfpMath
- computes the cosine of the argument.
- cos() -
Method in interface org.apache.commons.math3.RealFieldElement
- Cosine operation.
- cos() -
Method in class org.apache.commons.math3.util.Decimal64
- Cosine operation.
- cos(double) -
Static method in class org.apache.commons.math3.util.FastMath
- Cosine function.
- cosh() -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- Hyperbolic cosine operation.
- cosh(double[], int, double[], int) -
Method in class org.apache.commons.math3.analysis.differentiation.DSCompiler
- Compute hyperbolic cosine of a derivative structure.
- Cosh - Class in org.apache.commons.math3.analysis.function
- Hyperbolic cosine function.
- Cosh() -
Constructor for class org.apache.commons.math3.analysis.function.Cosh
-
- cosh() -
Method in class org.apache.commons.math3.complex.Complex
- Compute the
hyperbolic cosine of this complex number.
- cosh() -
Method in class org.apache.commons.math3.dfp.Dfp
- Hyperbolic cosine operation.
- cosh() -
Method in interface org.apache.commons.math3.RealFieldElement
- Hyperbolic cosine operation.
- cosh() -
Method in class org.apache.commons.math3.util.Decimal64
- Hyperbolic cosine operation.
- cosh(double) -
Static method in class org.apache.commons.math3.util.FastMath
- Compute the hyperbolic cosine of a number.
- cosine(RealVector) -
Method in class org.apache.commons.math3.linear.RealVector
- Computes the cosine of the angle between this vector and the
argument.
- cosInternal(Dfp[]) -
Static method in class org.apache.commons.math3.dfp.DfpMath
- Computes cos(a) Used when 0 < a < pi/4.
- cost -
Variable in class org.apache.commons.math3.optimization.general.AbstractLeastSquaresOptimizer
- Deprecated. As of 3.1. Field to become "private" in 4.0.
Please use
AbstractLeastSquaresOptimizer.setCost(double).
- Covariance - Class in org.apache.commons.math3.stat.correlation
- Computes covariances for pairs of arrays or columns of a matrix.
- Covariance() -
Constructor for class org.apache.commons.math3.stat.correlation.Covariance
- Create a Covariance with no data
- Covariance(double[][], boolean) -
Constructor for class org.apache.commons.math3.stat.correlation.Covariance
- Create a Covariance matrix from a rectangular array
whose columns represent covariates.
- Covariance(double[][]) -
Constructor for class org.apache.commons.math3.stat.correlation.Covariance
- Create a Covariance matrix from a rectangular array
whose columns represent covariates.
- Covariance(RealMatrix, boolean) -
Constructor for class org.apache.commons.math3.stat.correlation.Covariance
- Create a covariance matrix from a matrix whose columns
represent covariates.
- Covariance(RealMatrix) -
Constructor for class org.apache.commons.math3.stat.correlation.Covariance
- Create a covariance matrix from a matrix whose columns
represent covariates.
- covariance(double[], double[], boolean) -
Method in class org.apache.commons.math3.stat.correlation.Covariance
- Computes the covariance between the two arrays.
- covariance(double[], double[]) -
Method in class org.apache.commons.math3.stat.correlation.Covariance
- Computes the covariance between the two arrays, using the bias-corrected
formula.
- covarianceToCorrelation(RealMatrix) -
Method in class org.apache.commons.math3.stat.correlation.PearsonsCorrelation
- Derives a correlation matrix from a covariance matrix.
- create(RealLinearOperator) -
Static method in class org.apache.commons.math3.linear.JacobiPreconditioner
- Creates a new instance of this class.
- createAdaptor(RandomGenerator) -
Static method in class org.apache.commons.math3.random.RandomAdaptor
- Factory method to create a
Random using the supplied
RandomGenerator.
- createBlocksLayout(Field<T>, int, int) -
Static method in class org.apache.commons.math3.linear.BlockFieldMatrix
- Create a data array in blocks layout.
- createBlocksLayout(int, int) -
Static method in class org.apache.commons.math3.linear.BlockRealMatrix
- Create a data array in blocks layout.
- createChebyshevPolynomial(int) -
Static method in class org.apache.commons.math3.analysis.polynomials.PolynomialsUtils
- Create a Chebyshev polynomial of the first kind.
- createColumnFieldMatrix(T[]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Creates a column
FieldMatrix using the data from the input
array.
- createColumnRealMatrix(double[]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Creates a column
RealMatrix using the data from the input
array.
- createComplex(double, double) -
Method in class org.apache.commons.math3.complex.Complex
- Create a complex number given the real and imaginary parts.
- createComplexArray(double[][]) -
Static method in class org.apache.commons.math3.transform.TransformUtils
- Builds a new array of
Complex from the specified two dimensional
array of real and imaginary parts.
- createContributingStatistics() -
Method in class org.apache.commons.math3.stat.descriptive.AggregateSummaryStatistics
- Creates and returns a
SummaryStatistics whose data will be
aggregated with those of this AggregateSummaryStatistics.
- createFieldDiagonalMatrix(T[]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Returns a diagonal matrix with specified elements.
- createFieldIdentityMatrix(Field<T>, int) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Returns
dimension x dimension identity matrix.
- createFieldMatrix(Field<T>, int, int) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Returns a
FieldMatrix with specified dimensions.
- createFieldMatrix(T[][]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Returns a
FieldMatrix whose entries are the the values in the
the input array.
- createFieldVector(T[]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Creates a
FieldVector using the data from the input array.
- createHermitePolynomial(int) -
Static method in class org.apache.commons.math3.analysis.polynomials.PolynomialsUtils
- Create a Hermite polynomial.
- createJacobiPolynomial(int, int, int) -
Static method in class org.apache.commons.math3.analysis.polynomials.PolynomialsUtils
- Create a Jacobi polynomial.
- createLaguerrePolynomial(int) -
Static method in class org.apache.commons.math3.analysis.polynomials.PolynomialsUtils
- Create a Laguerre polynomial.
- createLegendrePolynomial(int) -
Static method in class org.apache.commons.math3.analysis.polynomials.PolynomialsUtils
- Create a Legendre polynomial.
- createMatrix(int, int) -
Method in class org.apache.commons.math3.linear.AbstractFieldMatrix
- Create a new FieldMatrix
of the same type as the instance with
the supplied row and column dimensions.
- createMatrix(int, int) -
Method in class org.apache.commons.math3.linear.AbstractRealMatrix
- Create a new RealMatrix of the same type as the instance with the
supplied
row and column dimensions.
- createMatrix(int, int) -
Method in class org.apache.commons.math3.linear.Array2DRowFieldMatrix
- Create a new FieldMatrix
of the same type as the instance with
the supplied row and column dimensions.
- createMatrix(int, int) -
Method in class org.apache.commons.math3.linear.Array2DRowRealMatrix
- Create a new RealMatrix of the same type as the instance with the
supplied
row and column dimensions.
- createMatrix(int, int) -
Method in class org.apache.commons.math3.linear.BlockFieldMatrix
- Create a new FieldMatrix
of the same type as the instance with
the supplied row and column dimensions.
- createMatrix(int, int) -
Method in class org.apache.commons.math3.linear.BlockRealMatrix
- Create a new RealMatrix of the same type as the instance with the
supplied
row and column dimensions.
- createMatrix(int, int) -
Method in class org.apache.commons.math3.linear.DiagonalMatrix
- Create a new RealMatrix of the same type as the instance with the
supplied
row and column dimensions.
- createMatrix(int, int) -
Method in interface org.apache.commons.math3.linear.FieldMatrix
- Create a new FieldMatrix
of the same type as the instance with
the supplied row and column dimensions.
- createMatrix(int, int) -
Method in class org.apache.commons.math3.linear.OpenMapRealMatrix
- Deprecated. Create a new RealMatrix of the same type as the instance with the
supplied
row and column dimensions.
- createMatrix(int, int) -
Method in interface org.apache.commons.math3.linear.RealMatrix
- Create a new RealMatrix of the same type as the instance with the
supplied
row and column dimensions.
- createMatrix(int, int) -
Method in class org.apache.commons.math3.linear.SparseFieldMatrix
- Deprecated. Create a new FieldMatrix
of the same type as the instance with
the supplied row and column dimensions.
- createRealDiagonalMatrix(double[]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Returns a diagonal matrix with specified elements.
- createRealIdentityMatrix(int) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Returns
dimension x dimension identity matrix.
- createRealImaginaryArray(Complex[]) -
Static method in class org.apache.commons.math3.transform.TransformUtils
- Builds a new two dimensional array of
double filled with the real
and imaginary parts of the specified Complex numbers.
- createRealMatrix(int, int) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Returns a
RealMatrix with specified dimensions.
- createRealMatrix(double[][]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Returns a
RealMatrix whose entries are the the values in the
the input array.
- createRealVector(double[]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Creates a
RealVector using the data from the input array.
- createRowFieldMatrix(T[]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Create a row
FieldMatrix using the data from the input
array.
- createRowRealMatrix(double[]) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Create a row
RealMatrix using the data from the input
array.
- crossover(Chromosome, Chromosome) -
Method in interface org.apache.commons.math3.genetics.CrossoverPolicy
- Perform a crossover operation on the given chromosomes.
- crossover(Chromosome, Chromosome) -
Method in class org.apache.commons.math3.genetics.CycleCrossover
- Perform a crossover operation on the given chromosomes.
- crossover(Chromosome, Chromosome) -
Method in class org.apache.commons.math3.genetics.NPointCrossover
- Performs a N-point crossover.
- crossover(Chromosome, Chromosome) -
Method in class org.apache.commons.math3.genetics.OnePointCrossover
- Performs one point crossover.
- crossover(Chromosome, Chromosome) -
Method in class org.apache.commons.math3.genetics.OrderedCrossover
- Perform a crossover operation on the given chromosomes.
- crossover(Chromosome, Chromosome) -
Method in class org.apache.commons.math3.genetics.UniformCrossover
- Perform a crossover operation on the given chromosomes.
- CrossoverPolicy - Interface in org.apache.commons.math3.genetics
- Policy used to create a pair of new chromosomes by performing a crossover
operation on a source pair of chromosomes.
- crossProduct(FieldVector3D<T>) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.FieldVector3D
- Compute the cross-product of the instance with another vector.
- crossProduct(Vector3D) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.FieldVector3D
- Compute the cross-product of the instance with another vector.
- crossProduct(FieldVector3D<T>, FieldVector3D<T>) -
Static method in class org.apache.commons.math3.geometry.euclidean.threed.FieldVector3D
- Compute the cross-product of two vectors.
- crossProduct(FieldVector3D<T>, Vector3D) -
Static method in class org.apache.commons.math3.geometry.euclidean.threed.FieldVector3D
- Compute the cross-product of two vectors.
- crossProduct(Vector3D, FieldVector3D<T>) -
Static method in class org.apache.commons.math3.geometry.euclidean.threed.FieldVector3D
- Compute the cross-product of two vectors.
- crossProduct(Vector<Euclidean3D>) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.Vector3D
- Compute the cross-product of the instance with another vector.
- crossProduct(Vector3D, Vector3D) -
Static method in class org.apache.commons.math3.geometry.euclidean.threed.Vector3D
- Compute the cross-product of two vectors.
- cumulativeProbability(int, int) -
Method in class org.apache.commons.math3.distribution.AbstractIntegerDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(x0 < X <= x1).
- cumulativeProbability(double, double) -
Method in class org.apache.commons.math3.distribution.AbstractRealDistribution
- Deprecated. As of 3.1 (to be removed in 4.0). Please use
AbstractRealDistribution.probability(double,double) instead.
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.BetaDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(int) -
Method in class org.apache.commons.math3.distribution.BinomialDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.CauchyDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.ChiSquaredDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(int) -
Method in class org.apache.commons.math3.distribution.EnumeratedIntegerDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.EnumeratedRealDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.ExponentialDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.FDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.GammaDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(int) -
Method in class org.apache.commons.math3.distribution.HypergeometricDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(int) -
Method in interface org.apache.commons.math3.distribution.IntegerDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(int, int) -
Method in interface org.apache.commons.math3.distribution.IntegerDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(x0 < X <= x1).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.LevyDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.LogNormalDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double, double) -
Method in class org.apache.commons.math3.distribution.LogNormalDistribution
- Deprecated. See
RealDistribution.cumulativeProbability(double,double)
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.NormalDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double, double) -
Method in class org.apache.commons.math3.distribution.NormalDistribution
- Deprecated. See
RealDistribution.cumulativeProbability(double,double)
- cumulativeProbability(int) -
Method in class org.apache.commons.math3.distribution.PascalDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(int) -
Method in class org.apache.commons.math3.distribution.PoissonDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in interface org.apache.commons.math3.distribution.RealDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double, double) -
Method in interface org.apache.commons.math3.distribution.RealDistribution
- Deprecated. As of 3.1. In 4.0, this method will be renamed
probability(double x0, double x1).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.TDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.TriangularDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(int) -
Method in class org.apache.commons.math3.distribution.UniformIntegerDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.UniformRealDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.distribution.WeibullDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(int) -
Method in class org.apache.commons.math3.distribution.ZipfDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- cumulativeProbability(double) -
Method in class org.apache.commons.math3.random.EmpiricalDistribution
- For a random variable
X whose values are distributed according
to this distribution, this method returns P(X <= x).
- currentState -
Variable in class org.apache.commons.math3.ode.sampling.AbstractStepInterpolator
- current state
- CurveFitter<T extends ParametricUnivariateFunction> - Class in org.apache.commons.math3.fitting
- Fitter for parametric univariate real functions y = f(x).
- CurveFitter(MultivariateVectorOptimizer) -
Constructor for class org.apache.commons.math3.fitting.CurveFitter
- Simple constructor.
- CurveFitter<T extends ParametricUnivariateFunction> - Class in org.apache.commons.math3.optimization.fitting
- Deprecated. As of 3.1 (to be removed in 4.0).
- CurveFitter(DifferentiableMultivariateVectorOptimizer) -
Constructor for class org.apache.commons.math3.optimization.fitting.CurveFitter
- Deprecated. as of 3.1 replaced by
CurveFitter.CurveFitter(MultivariateDifferentiableVectorOptimizer)
- CurveFitter(MultivariateDifferentiableVectorOptimizer) -
Constructor for class org.apache.commons.math3.optimization.fitting.CurveFitter
- Deprecated. Simple constructor.
- CycleCrossover<T> - Class in org.apache.commons.math3.genetics
- Cycle Crossover [CX] builds offspring from ordered chromosomes by identifying cycles
between two parent chromosomes.
- CycleCrossover() -
Constructor for class org.apache.commons.math3.genetics.CycleCrossover
- Creates a new
CycleCrossover policy.
- CycleCrossover(boolean) -
Constructor for class org.apache.commons.math3.genetics.CycleCrossover
- Creates a new
CycleCrossover policy using the given randomStart behavior.
DBSCANClusterer insteaddouble value in an object.sequence of objects of type T according to the
permutation this chromosome represents.
sequence of objects of type T according to the
permutation this chromosome represents.
CMAESOptimizer.checkFeasableCount: 0.
CMAESOptimizer.diagonalOnly: 0.
RealMatrix objects.
BOBYQAOptimizer.initialTrustRegionRadius: 10.0 .
BOBYQAOptimizer.initialTrustRegionRadius: 10.0 .
CMAESOptimizer.isActiveCMA: true.
CMAESOptimizer.maxIterations: 30000.
CMAESOptimizer.random.
CMAESOptimizer.stopFitness: 0.0.
BOBYQAOptimizer.stoppingTrustRegionRadius: 1.0E-8 .
BOBYQAOptimizer.stoppingTrustRegionRadius: 1.0E-8 .
FieldMatrixChangingVisitor interface.FieldMatrixPreservingVisitor interface.IterativeLinearSolverEvent.MeasurementModel for the use with a KalmanFilter.MeasurementModel, taking double arrays as input parameters for the
respective measurement matrix and noise.
MeasurementModel, taking RealMatrix objects
as input parameters for the respective measurement matrix and noise.
ProcessModel for the use with a KalmanFilter.ProcessModel, taking double arrays as input parameters.
ProcessModel, taking double arrays as input parameters.
ProcessModel, taking double arrays as input parameters.
RealMatrixChangingVisitor interface.RealMatrixPreservingVisitor interface.x.
x.
x.
X whose values are distributed according to
this distribution, this method returns P(X = x).
x.
x.
x.
x.
x.
x.
x.
x.
x.
x.
x.
x.
x.
x.
x.
Acos.value(DerivativeStructure)
Acosh.value(DerivativeStructure)
Asin.value(DerivativeStructure)
Asinh.value(DerivativeStructure)
Atan.value(DerivativeStructure)
Atanh.value(DerivativeStructure)
Cbrt.value(DerivativeStructure)
Constant.value(DerivativeStructure)
Cos.value(DerivativeStructure)
Cosh.value(DerivativeStructure)
Exp.value(DerivativeStructure)
Expm1.value(DerivativeStructure)
Gaussian.value(DerivativeStructure)
HarmonicOscillator.value(DerivativeStructure)
Identity.value(DerivativeStructure)
Inverse.value(DerivativeStructure)
Log.value(DerivativeStructure)
Log10.value(DerivativeStructure)
Log1p.value(DerivativeStructure)
Logistic.value(DerivativeStructure)
Logit.value(DerivativeStructure)
Minus.value(DerivativeStructure)
Power.value(DerivativeStructure)
Sigmoid.value(DerivativeStructure)
Sin.value(DerivativeStructure)
Sinc.value(DerivativeStructure)
Sinh.value(DerivativeStructure)
Sqrt.value(DerivativeStructure)
Tan.value(DerivativeStructure)
Tanh.value(DerivativeStructure)
UnivariateFunction.
RealMatrix field in a class.
RealVector field in a class.
Dfp which hides the radix-10000 artifacts of the superclass.Dfp.MultivariateDifferentiableFunctionMultivariateDifferentiableVectorFunctionUnivariateDifferentiableFunctionUnivariateDifferentiableMatrixFunctionUnivariateDifferentiableSolverUnivariateDifferentiableVectorFunctiondifferential from a regular function.
differential from a regular vector function.
differential from a regular matrix function.
differential from a regular function.
differential from a regular matrix function.
differential from a regular vector function.
i initial elements of the array.
i last elements of the array.
Clusterable instances
with the configured DistanceMeasure.
Complex whose value is
(this / divisor).
Complex whose value is (this / divisor),
with divisor interpreted as a real number.
BigInteger,
ie this * 1 / bg, returning the result in reduced form.
int, ie
this * 1 / i, returning the result in reduced form.
long, ie
this * 1 / l, returning the result in reduced form.
v.
v.
Clusterable for points with double coordinates.Localizable interface, without localization.RealVector might lead to wrong results. Since there is no
satisfactory correction to this bug, this method is deprecated. Users who
want to preserve this feature are advised to implement
RealVectorPreservingVisitor (possibly ignoring corner cases for
the sake of efficiency).
RealVector might lead to wrong results. Since there is no
satisfactory correction to this bug, this method is deprecated. Users who
want to preserve this feature are advised to implement
RealVectorPreservingVisitor (possibly ignoring corner cases for
the sake of efficiency).
ElitisticListPopulation instance.
ElitisticListPopulation instance and initializes its inner chromosome list.
RandomGenerator as the source of random data.
RandomGenerator as the source of random data.
EmpiricalDistribution.EmpiricalDistribution(int,RandomGenerator) instead.
EmpiricalDistribution.EmpiricalDistribution(RandomGenerator) instead.
EnumeratedDistribution.EnumeratedDistribution.1 + EPSILON is numerically equal to 1.
object is a
FieldMatrix instance with the same dimensions as this
and all corresponding matrix entries are equal.
object is a
RealMatrix instance with the same dimensions as this
and all corresponding matrix entries are equal.
object is an
AbstractStorelessUnivariateStatistic returning the same
values as this for getResult() and getN()
object is a MultivariateSummaryStatistics
instance and all statistics have the same values as this.
object is a
StatisticalSummaryValues instance and all statistics have
the same values as this.
object is a
SummaryStatistics instance and all statistics have the
same values as this.
object is a MultivariateSummaryStatistics
instance and all statistics have the same values as this.
object is a
SummaryStatistics instance and all statistics have the
same values as this.
Precision.equals(float,float).
true iff both arguments are null or have same
dimensions and all their elements are equal as defined by
Precision.equals(double,double).
equals(x, y, 1).
equals(x, y, 1).
true if there is no double value strictly between the
arguments or the difference between them is within the range of allowed
error (inclusive).
this method.
true iff both arguments are null or have same
dimensions and all their elements are equal as defined by
this method.
equals(x, y, 1).
equals(x, y, maxUlps).
equals(x, y, 1).
equals(x, y, maxUlps).
true if there is no double value strictly between the
arguments or the reltaive difference between them is smaller or equal
to the given tolerance.
MultivariateNormalMixtureExpectationMaximization.fit(MixtureMultivariateNormalDistribution).
DoublePoint insteadDoublePoint insteadAbstractStorelessUnivariateStatistic.clear(), then invokes
AbstractStorelessUnivariateStatistic.increment(double) in a loop over the the input array, and then uses
AbstractStorelessUnivariateStatistic.getResult() to compute the return value.
AbstractStorelessUnivariateStatistic.clear(), then invokes
AbstractStorelessUnivariateStatistic.increment(double) in a loop over the specified portion of the input
array, and then uses AbstractStorelessUnivariateStatistic.getResult() to compute the return value.
Double.NaN if the designated subarray
is empty.
Double.NaN if the designated subarray
is empty.
SemiVariance of the designated values against the mean, using
instance properties varianceDirection and biasCorrection.
SemiVariance for the entire array against the mean, using
the current value of the biasCorrection instance property.
SemiVariance of the designated values against the cutoff, using
instance properties variancDirection and biasCorrection.
SemiVariance of the designated values against the cutoff in the
given direction, using the current value of the biasCorrection instance property.
SemiVariance of the designated values against the cutoff
in the given direction with the provided bias correction.
Double.NaN if the array is empty.
Double.NaN if the designated subarray
is empty.
Double.NaN if the array is empty.
Double.NaN if the designated subarray
is empty.
Double.NaN if the designated subarray
is empty.
Double.NaN if the designated subarray
is empty.
Double.NaN if the designated subarray
is empty.
pth percentile of the values
in the values array.
quantileth percentile of the
designated values in the values array.
pth percentile of the values
in the values array, starting with the element in (0-based)
position begin in the array and including length
values.
Double.NaN if the designated subarray
is empty.
Double.NaN if the designated subarray
is empty.
Double.NaN if the designated subarray
is empty.
Double.NaN if the designated subarray
is empty.
event handler.
event handler during integration steps.int.
ExceptionContext interface.ex-1 function.n.
Math and
StrictMath for large scale computation.Rotation using RealFieldElement.Vector3D using RealFieldElement.length with values generated
using getNext() repeatedly.
filtering events.population for another chromosome with the same representation.
PolynomialFitter.fit(double[]) instead.
FixedElapsedTime instance.
FixedElapsedTime instance.
float.
floor function.ComplexFormat.format(Object,StringBuffer,FieldPosition).
ComplexFormat.format(Object,StringBuffer,FieldPosition).
Complex object to produce a string.
BigFraction object to produce a string.
Fraction object to produce a string.
BigFraction object to produce a string.
Fraction object to produce a string.
Vector object to produce a string.
Vector3D object to produce a string.
Vector object to produce a string.
Vector object to produce a string.
Vector object to produce a string.
Vector to produce a string.
RealMatrixFormat.format(RealMatrix,StringBuffer,FieldPosition).
RealMatrix object to produce a string.
RealVectorFormat.format(RealVector,StringBuffer,FieldPosition).
RealVector object to produce a string.
FieldMatrix/Fraction matrix to a RealMatrix.
observed and expected
frequency counts.
Gaussian function.norm, mean, and sigma
of a Gaussian.Parametric
based on the specified observed points.norm, mean, and sigma
of a Gaussian.Parametric
based on the specified observed points.integrating a weighted
function.points and weights.
Gaussian integration rule.SimpleVectorValueChecker.SimpleVectorValueChecker()
SimpleVectorValueChecker.SimpleVectorValueChecker()
observed1 and observed2.
GeometricMean identical
to the original
Double.NaN if the array is empty.
Double.NaN if the designated subarray
is empty.
alpha.
GammaDistribution.getShape() should be preferred.
This method will be removed in version 4.0.
beta.
GammaDistribution.getScale() should be preferred.
This method will be removed in version 4.0.
SummaryStatistics instances containing
statistics describing the values in each of the bins.
true if positive-definiteness should be checked for both
matrix and preconditioner.
true if symmetry of the matrix, and symmetry as well as
positive definiteness of the preconditioner should be checked.
col as an array.
col as an array.
col as an array.
column
as a column matrix.
column
as a column matrix.
column
as a column matrix.
column
as a vector.
column
as a vector.
column
as a vector.
ResizableDoubleArray.getContractionCriterion()
instead.
AbstractLeastSquaresOptimizer.computeCovariances(double[],double)
instead.
AbstractLeastSquaresOptimizer.computeCovariances(double[],double)
instead.
CrossoverPolicy.
FieldVector.toArray() method instead.
SparseFieldVector.toArray() method instead.
BigInteger.
DistanceMeasure instance used by this clusterer.
DoubleArray.
ResizableArray.
EmpiricalDistribution used when operating in 0.
KMeansPlusPlusClusterer.EmptyClusterStrategy used by this instance.
ResizableDoubleArray.ExpansionMode in 4.0.
BracketFinder.getHi().
BracketFinder.getHi().
Field to which the instance belongs.
Field to which the instance belongs.
Field (really a DfpField) to which the instance belongs.
Field to which the instance belongs.
Field to which the instance belongs.
Field to which the instance belongs.
Field to which the instance belongs.
Field to which the instance belongs.
BracketFinder.getLo().
BracketFinder.getLo().
BracketFinder.getMid().
BracketFinder.getMid().
StoppingCondition in the last run.
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
k-th n-th root of unity.
SimpleRegression.hasIntercept() is true; otherwise 0.
this event
is created.
Interval.getSize()
Interval.getInf()
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
Interval.getBarycenter()
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
c of this distribution.
ValueServer.GAUSSIAN_MODE, ValueServer.EXPONENTIAL_MODE
or ValueServer.UNIFORM_MODE.
Covariance method is not supported by a StorelessCovariance,
since the number of bivariate observations does not have to be the same for different
pairs of covariates - i.e., N as defined in Covariance.getN() is undefined.
BigInteger.
optimize.
optimize.
optimize.
optimize.
optimize.
optimize.
optimize.
index.
index.
Dfp instances built by this factory.
PearsonsCorrelation instance constructed from the
ranked input data.
CrossoverPolicy.
k-th n-th root of unity.
BigFraction instance with the 2 parts of a fraction
Y/Z.
Fraction instance with the 2 parts
of a fraction Y/Z.
RoundingMode.HALF_UP
row as an array.
row as an array.
row as an array.
row
as a row matrix.
row
as a row matrix.
row
as a row matrix.
row
as a vector.
row as a vector.
row
as a vector.
row as a vector.
row
as a vector.
row as a vector.
StatisticalSummary describing this distribution.
this distribution.
beta.
this distribution.
alpha.
ValueServer.GAUSSIAN_MODE.
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
StatisticalSummaryValues instance reporting current
aggregate statistics.
StatisticalSummaryValues instance reporting current
statistics.
StatisticalSummaryValues instance reporting current
statistics.
MultivariateSummaryStatistics.addValue(double[])
MultivariateSummaryStatistics.addValue(double[])
Transform embedding an affine transform.
Interval.getSup()
ValueServer.DIGEST_MODE.
x.
x.
x.
x.
x.
observed frequency counts to those in the expected array.
alpha.
observed1 and
observed2.
AbstractLeastSquaresOptimizer.computeSigma(double[],double) should be used
instead. It should be emphasized that guessParametersErrors and
computeSigma are not strictly equivalent.
new Double(this.doubleValue()).hashCode()
StatisticalSummary instances, under the
assumption of equal subpopulation variances.
sample1
and sample2 are drawn from populations with the same mean,
with significance level alpha, assuming that the
subpopulation variances are equal.
this and y
- sqrt(this2 +y2)x and y
- sqrt(x2 +y2)this and y
- sqrt(this2 +y2)this and y
- sqrt(this2 +y2)this and y
- sqrt(this2 +y2)x and y
- sqrt(x2 +y2)RealLinearOperator is too high.Variance.increment(double) should increment
the internal second moment.
AbstractStorelessUnivariateStatistic.increment(double) in a loop over
the input array.
AbstractStorelessUnivariateStatistic.increment(double) in a loop over
the specified portion of the input array.
MaxCountExceededException.permutedData when applied to
originalData.
EnumeratedDistribution instance (using the Integer wrapper)
used to generate the pmf.
EnumeratedDistribution (using the Double wrapper)
used to generate the pmf.
f(x) * w(x),
where w is a weight function that depends on the actual
flavor of the Gauss integration scheme.
SplineInterpolator
on the resulting fit.
int.
true if RootsOfUnity.computeRoots(int) was called with a
positive value of its argument n.
Double.POSITIVE_INFINITY or
Double.NEGATIVE_INFINITY) and neither part
is NaN.
NaN.
NaN.
NaN.
true if this double precision number is infinite
(Double.POSITIVE_INFINITY or Double.NEGATIVE_INFINITY).
NaN.
NaN.
NaN.
NaN.
true if this double precision number is
Not-a-Number (NaN), false otherwise.
true iff another has the same representation and therefore the same fitness.
true iff another is a RandomKey and
encodes the same permutation.
true if this operator supports
RealLinearOperator.operateTranspose(RealVector).
IterationManager should be derived.IterativeLinearSolver.secondary equations to
compute the Jacobian matrices with respect to the initial state vector and, if
any, to some parameters of the primary ODE set.java.util.Random to implement
RandomGenerator.KMeansPlusPlusClusterer insteadKurtosis identical
to the original
g constant in the Lanczos approximation, see
Gamma.lanczos(double).
lcm(a,b) = (a / gcd(a,b)) * b.
lcm(a,b) = (a / gcd(a,b)) * b.
vectorial objective functions to
scalar objective functions
when the goal is to minimize them.integrate method will perform an integration on the natural interval
[-1 , 1].
integrate method will perform an integration on the given interval.
IterativeLegendreGaussIntegrator instead.integrate method will perform an integration on the natural interval
[-1 , 1].
integrate method will perform an integration on the given interval.
DECIMAL128.
other contructor.
other contructor.
other contructor.
other contructor.
linear constraints.List.LoessInterpolator
with a bandwidth of LoessInterpolator.DEFAULT_BANDWIDTH,
LoessInterpolator.DEFAULT_ROBUSTNESS_ITERS robustness iterations
and an accuracy of {#link #DEFAULT_ACCURACY}.
LoessInterpolator
with given bandwidth and number of robustness iterations.
LoessInterpolator
with given bandwidth, number of robustness iterations and accuracy.
Dfp.intLog10(), in 4.0 the return type
will be changed to Dfp
log(1 + p) function.Beta.logBeta(double, double).
normally distributed natural
logarithm of the log-normal distribution are equal to zero and one
respectively.
long.
first order
differential equations in order to compute exactly the main state jacobian
matrix for partial derivatives equations.CycleCrossover.crossover(Chromosome, Chromosome).
OrderedCrossover.crossover(Chromosome, Chromosome).
NullArgumentException) inherit from this class.Max identical
to the original
Double.NaN if the array is empty.
Double.NaN if the designated subarray
is empty.
Mean identical
to the original
Double.NaN if the array is empty.
Double.NaN if the designated subarray
is empty.
KalmanFilter.Median identical
to the original
Collection of Frequency objects into this instance.
UpdatingMultipleLinearRegression interface.Min identical
to the original
Double.NaN if the array is empty.
Double.NaN if the designated subarray
is empty.
ResizableDoubleArray.ExpansionMode.MULTIPLICATIVE instead.
FunctionUtils.multiply(UnivariateDifferentiableFunction...)
Complex whose value is this * factor.
Complex whose value is this * factor, with factor
interpreted as a integer number.
Complex whose value is this * factor, with factor
interpreted as a real number.
BigInteger, returning the result in reduced form.
m.
this by m.
m.
this by m.
m.
this by m.
this by m.
m.
this by m.
this by m.
m.
this by m.
m.
this by m.
this matrix by the
specified value.
this matrix by the
specified value.
this matrix by the
specified value.
this matrix by the
specified value.
this matrix by the
specified value.
this matrix by the
specified value.
UnivariateOptimizer interface
adding multi-start features to an existing optimizer.MultivariateFunction representing a
multivariate differentiable real function.MultivariateVectorFunction representing a
multivariate differentiable vectorial function.MultivariateFunction to unbounded ones.MultivariateFunction to an unbouded
domain using a penalty function.addValue method.Double.NaN as a Decimal64.
this element.
Complex whose value is (-this).
this element.
this element.
this element.
Double.NEGATIVE_INFINITY as a
Decimal64.
Dfp with a value of 0.
Dfp given a String representation.
Dfp with a non-finite value.
this is, with a given arrayRepresentation.
NewtonRaphsonSolverBeta Distribution.
Beta Distribution.
Binomial Distribution.
Binomial Distribution.
boolean value from this random number generator's
sequence.
boolean value from this random number generator's
sequence.
boolean value from this random number generator's
sequence.
boolean value from this random number generator's
sequence.
boolean value from this random number generator's
sequence.
Cauchy Distribution.
Cauchy Distribution.
ChiSquare Distribution.
ChiSquare Distribution.
double value between 0.0 and
1.0 from this random number generator's sequence.
double value between 0.0 and
1.0 from this random number generator's sequence.
double value between 0.0 and
1.0 from this random number generator's sequence.
double value between 0.0 and
1.0 from this random number generator's sequence.
double value between 0.0 and
1.0 from this random number generator's sequence.
F Distribution.
F Distribution.
float
value between 0.0 and 1.0 from this random
number generator's sequence.
float
value between 0.0 and 1.0 from this random
number generator's sequence.
float
value between 0.0 and 1.0 from this random
number generator's sequence.
float
value between 0.0 and 1.0 from this random
number generator's sequence.
float
value between 0.0 and 1.0 from this random
number generator's sequence.
Gamma Distribution.
Gamma Distribution.
double value with mean 0.0 and standard
deviation 1.0 from this random number generator's sequence.
double value with mean 0.0 and standard
deviation 1.0 from this random number generator's sequence.
double value with mean 0.0 and standard
deviation 1.0 from this random number generator's sequence.
double value with mean 0.0 and standard
deviation 1.0 from this random number generator's sequence.
double value with mean 0.0 and standard
deviation 1.0 from this random number generator's sequence.
len.
len.
len.
Hypergeometric Distribution.
Hypergeometric Distribution.
int
value from this random number generator's sequence.
int value
between 0 (inclusive) and the specified value (exclusive), drawn from
this random number generator's sequence.
int
value from this random number generator's sequence.
int
value from this random number generator's sequence.
lower
and upper (endpoints included).
lower
and upper (endpoints included).
lower
and upper (endpoints included).
int
value from this random number generator's sequence.
int
value from this random number generator's sequence.
long
value from this random number generator's sequence.
long
value from this random number generator's sequence.
long
value from this random number generator's sequence.
lower and upper (endpoints included).
lower and upper (endpoints included).
lower and upper (endpoints included).
long
value from this random number generator's sequence.
long
value from this random number generator's sequence.
Pascal Distribution.
Pascal Distribution.
k whose entries are selected
randomly, without repetition, from the integers 0, ..., n - 1
(inclusive).
k whose entries are selected
randomly, without repetition, from the integers 0, ..., n - 1
(inclusive).
k whose entries are selected
randomly, without repetition, from the integers 0, ..., n - 1
(inclusive).
k objects selected randomly from the
Collection c.
k objects selected randomly from the
Collection c.
k objects selected randomly from the
Collection c.
lower
and upper (endpoints included) from a secure random sequence.
lower
and upper (endpoints included) from a secure random sequence.
lower
and upper (endpoints included) from a secure random sequence.
lower and upper (endpoints included) from a secure random
sequence.
lower and upper (endpoints included) from a secure random
sequence.
lower and upper (endpoints included) from a secure random
sequence.
T Distribution.
T Distribution.
(lower, upper) (i.e., endpoints excluded).
(lower, upper) or the interval [lower, upper).
(lower, upper) (i.e., endpoints excluded).
(lower, upper) or the interval [lower, upper).
(lower, upper) (i.e., endpoints excluded).
(lower, upper) or the interval [lower, upper).
Weibull Distribution.
Weibull Distribution.
Zipf Distribution.
Zipf Distribution.
line search solver and
preconditioner.
preconditioner.
SimpleValueChecker.SimpleValueChecker()
line search solver and
preconditioner.
preconditioner.
RealLinearOperator is expected.RealLinearOperator
is expected.NPointCrossover policy using the given number of points.
null argument must throw
this exception.RealMatrix objects compatible with octave.
1d as a Decimal64.
Entry optimized for OpenMap.v.
v.
v.
this by the vector x.
v.
v.
v.
v.
v.
v.
v.
this by the vector x.
this by the vector x.
v.
v.
this operator
by the vector x (optional operation).
method.
method.
BaseAbstractMultivariateOptimizer.optimize(int,MultivariateFunction,GoalType,OptimizationData[])
instead.
BaseAbstractMultivariateVectorOptimizer.optimize(int,MultivariateVectorFunction,OptimizationData[])
instead.
optimize(int,MultivariateDifferentiableVectorFunction,OptimizationData...)
instead.
optimize(int,MultivariateDifferentiableVectorFunction,OptimizationData...)
instead.
BaseAbstractMultivariateOptimizer.optimize(int,MultivariateFunction,GoalType,OptimizationData[])
instead.
BaseAbstractMultivariateVectorOptimizer.optimizeInternal(int,MultivariateVectorFunction,OptimizationData[])
instead.
AbstractDifferentiableOptimizer.optimizeInternal(int,MultivariateDifferentiableFunction,GoalType,OptimizationData[])
instead.
MultivariateDifferentiableVectorFunction.
function package contains function objects that wrap the
methods contained in Math, as well as common
mathematical functions such as the gaussian and sinc functions.minimize or
maximize
a scalar function, called the
objective
function.polyhedrons sets outlines.sample1 and
sample2 is 0 in favor of the two-sided alternative that the
mean paired difference is not equal to 0, with significance level
alpha.
partial derivatives equations.partial derivatives equations.Complex object.
Complex object.
BigFraction object.
BigFraction object.
Fraction object.
Fraction object.
BigFraction object.
Fraction object.
Vector object.
Vector object.
Vector3D object.
Vector3D object.
Vector object.
Vector object.
Vector object.
Vector object.
RealMatrix object.
RealMatrix object.
RealVector object.
RealVector object.
source until a non-whitespace character is found.
source until a non-whitespace character is found.
source for an expected fixed string.
BigInteger.
source until a non-whitespace character is found.
source until a non-whitespace character is found.
source for a number.
Covariance.
Percentile identical
to the original
pth percentile of the values
in the values array.
pth percentile of the values
in the values array, starting with the element in (0-based)
position begin in the array and including length
values.
PolynomialFunction.
curve fitting.PolynomialFitter.PolynomialFitter(DifferentiableMultivariateVectorOptimizer) instead.
Double.NaN if the array is empty.
Double.NaN if the designated subarray
is empty.
Double.POSITIVE_INFINITY as a
Decimal64.
x.
x.
BigFraction whose value is
(this<sup>exponent</sup>), returning the result in reduced form.
BigFraction whose value is
(thisexponent), returning the result in reduced form.
BigFraction whose value is
(thisexponent), returning the result in reduced form.
double whose value is
(thisexponent), returning the result in reduced form.
p times.
this with itself p
times.
p times.
this with itself p
times.
y value associated with the
supplied x value, based on the data that has been
added to the model when this method is activated.
m.
v.
v.
this by m.
v.
v.
v.
v.
v.
v.
v.
m.
v.
v.
this by m.
v.
v.
int:
primality test
prime number generation
factorization
X whose values are distributed according
to this distribution, this method returns P(x0 < X <= x1).
X whose values are distributed according
to this distribution, this method returns P(X = x).
X whose values are distributed according
to this distribution, this method returns P(X = x).
X whose values are distributed according
to this distribution, this method returns P(X = x).
X whose values are distributed according
to this distribution, this method returns P(X = x).
X whose values are distributed according
to this distribution, this method returns P(X = x).
X whose values are distributed according
to this distribution, this method returns P(X = x).
X whose values are distributed according
to this distribution, this method returns P(x0 < X <= x1).
X whose values are distributed according
to this distribution, this method returns P(x0 < X <= x1).
X whose values are distributed according
to this distribution, this method returns P(X = x).
X whose values are distributed according
to this distribution, this method returns P(X = x).
X whose values are distributed according
to this distribution, this method returns P(X = x).
X whose values are distributed according
to this distribution, this method returns P(X = x).
X whose values are distributed according
to this distribution, this method returns P(X = x).
X whose values are distributed according
to this distribution, this method returns P(X = x).
KalmanFilter.Product identical
to the original
Double.NaN if the array is empty.
Double.NaN if the designated subarray
is empty.
true if IterativeLinearSolverEvent.getResidual() is supported.
true if IterativeLinearSolverEvent.getResidual() is supported.
java.util.Random wrapping a
RandomGenerator.length.
AbstractIntegerDistribution.random instance variable instead.
AbstractRealDistribution.random instance variable instead.
RandomDataGenerator directlyRandomData interface using a RandomGenerator
instance to generate non-secure data and a SecureRandom
instance to provide data for the nextSecureXxx methods.RandomGenerator as
the source of (non-secure) random data.
RandomDataGenerator insteadRandomGenerator as
the source of (non-secure) random data.
java.util.Random.RandomKeys.data using the natural ordering on Doubles, with
NaN values handled according to nanStrategy and ties
resolved using tiesStrategy.
- rank(double[]) -
Method in interface org.apache.commons.math3.stat.ranking.RankingAlgorithm
- Performs a rank transformation on the input data, returning an array
of ranks.
- RankingAlgorithm - Interface in org.apache.commons.math3.stat.ranking
- Interface representing a rank transformation.
- readBaseExternal(ObjectInput) -
Method in class org.apache.commons.math3.ode.sampling.AbstractStepInterpolator
- Read the base state of the instance.
- readExternal(ObjectInput) -
Method in class org.apache.commons.math3.ode.sampling.AbstractStepInterpolator
-
- readExternal(ObjectInput) -
Method in class org.apache.commons.math3.ode.sampling.NordsieckStepInterpolator
-
- readResolve() -
Method in class org.apache.commons.math3.complex.Complex
- Resolve the transient fields in a deserialized Complex Object.
- RealDistribution - Interface in org.apache.commons.math3.distribution
- Base interface for distributions on the reals.
- RealFieldElement<T> - Interface in org.apache.commons.math3
- Interface representing a real
field.
- RealLinearOperator - Class in org.apache.commons.math3.linear
- This class defines a linear operator operating on real (
double)
vector spaces. - RealLinearOperator() -
Constructor for class org.apache.commons.math3.linear.RealLinearOperator
-
- RealMatrix - Interface in org.apache.commons.math3.linear
- Interface defining a real-valued matrix with basic algebraic operations.
- RealMatrixChangingVisitor - Interface in org.apache.commons.math3.linear
- Interface defining a visitor for matrix entries.
- RealMatrixFormat - Class in org.apache.commons.math3.linear
- Formats a
nxm matrix in components list format
"{{a00,a01, ...,
a0m-1},{a10,
a11, ..., a1m-1},{...},{
an-10, an-11, ...,
an-1m-1}}". - RealMatrixFormat() -
Constructor for class org.apache.commons.math3.linear.RealMatrixFormat
- Create an instance with default settings.
- RealMatrixFormat(NumberFormat) -
Constructor for class org.apache.commons.math3.linear.RealMatrixFormat
- Create an instance with a custom number format for components.
- RealMatrixFormat(String, String, String, String, String, String) -
Constructor for class org.apache.commons.math3.linear.RealMatrixFormat
- Create an instance with custom prefix, suffix and separator.
- RealMatrixFormat(String, String, String, String, String, String, NumberFormat) -
Constructor for class org.apache.commons.math3.linear.RealMatrixFormat
- Create an instance with custom prefix, suffix, separator and format
for components.
- RealMatrixPreservingVisitor - Interface in org.apache.commons.math3.linear
- Interface defining a visitor for matrix entries.
- RealTransformer - Interface in org.apache.commons.math3.transform
- Interface for one-dimensional data sets transformations producing real results.
- RealVector - Class in org.apache.commons.math3.linear
- Class defining a real-valued vector with basic algebraic operations.
- RealVector() -
Constructor for class org.apache.commons.math3.linear.RealVector
-
- RealVector.Entry - Class in org.apache.commons.math3.linear
- An entry in the vector.
- RealVector.Entry() -
Constructor for class org.apache.commons.math3.linear.RealVector.Entry
- Simple constructor.
- RealVector.SparseEntryIterator - Class in org.apache.commons.math3.linear
- Deprecated. As of 3.1, this class is deprecated, see
JIRA MATH-875.
This class will be completely removed in 4.0.
- RealVector.SparseEntryIterator() -
Constructor for class org.apache.commons.math3.linear.RealVector.SparseEntryIterator
- Deprecated. Simple constructor.
- RealVectorChangingVisitor - Interface in org.apache.commons.math3.linear
- This interface defines a visitor for the entries of a vector.
- RealVectorFormat - Class in org.apache.commons.math3.linear
- Formats a vector in components list format "{v0; v1; ...; vk-1}".
- RealVectorFormat() -
Constructor for class org.apache.commons.math3.linear.RealVectorFormat
- Create an instance with default settings.
- RealVectorFormat(NumberFormat) -
Constructor for class org.apache.commons.math3.linear.RealVectorFormat
- Create an instance with a custom number format for components.
- RealVectorFormat(String, String, String) -
Constructor for class org.apache.commons.math3.linear.RealVectorFormat
- Create an instance with custom prefix, suffix and separator.
- RealVectorFormat(String, String, String, NumberFormat) -
Constructor for class org.apache.commons.math3.linear.RealVectorFormat
- Create an instance with custom prefix, suffix, separator and format
for components.
- RealVectorPreservingVisitor - Interface in org.apache.commons.math3.linear
- This interface defines a visitor for the entries of a vector.
- reciprocal() -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- Returns the multiplicative inverse of
this element.
- reciprocal() -
Method in class org.apache.commons.math3.complex.Complex
- Returns the multiplicative inverse of
this element.
- reciprocal() -
Method in class org.apache.commons.math3.dfp.Dfp
- Returns the multiplicative inverse of
this element.
- reciprocal() -
Method in interface org.apache.commons.math3.FieldElement
- Returns the multiplicative inverse of
this element.
- reciprocal() -
Method in class org.apache.commons.math3.fraction.BigFraction
-
Return the multiplicative inverse of this fraction.
- reciprocal() -
Method in class org.apache.commons.math3.fraction.Fraction
- Return the multiplicative inverse of this fraction.
- reciprocal() -
Method in interface org.apache.commons.math3.RealFieldElement
- Returns the multiplicative inverse of
this element.
- reciprocal() -
Method in class org.apache.commons.math3.util.BigReal
- Returns the multiplicative inverse of
this element.
- reciprocal() -
Method in class org.apache.commons.math3.util.Decimal64
- Returns the multiplicative inverse of
this element.
- RectangularCholeskyDecomposition - Class in org.apache.commons.math3.linear
- Calculates the rectangular Cholesky decomposition of a matrix.
- RectangularCholeskyDecomposition(RealMatrix) -
Constructor for class org.apache.commons.math3.linear.RectangularCholeskyDecomposition
- Decompose a symmetric positive semidefinite matrix.
- RectangularCholeskyDecomposition(RealMatrix, double) -
Constructor for class org.apache.commons.math3.linear.RectangularCholeskyDecomposition
- Decompose a symmetric positive semidefinite matrix.
- reduce() -
Method in class org.apache.commons.math3.fraction.BigFraction
-
Reduce this
BigFraction to its lowest terms.
- reduce(double, double, double) -
Static method in class org.apache.commons.math3.util.MathUtils
- Reduce
|a - offset| to the primary interval
[0, |period|).
- Region<S extends Space> - Interface in org.apache.commons.math3.geometry.partitioning
- This interface represents a region of a space as a partition.
- Region.Location - Enum in org.apache.commons.math3.geometry.partitioning
- Enumerate for the location of a point with respect to the region.
- RegionFactory<S extends Space> - Class in org.apache.commons.math3.geometry.partitioning
- This class is a factory for
Region. - RegionFactory() -
Constructor for class org.apache.commons.math3.geometry.partitioning.RegionFactory
- Simple constructor.
- registerVariationalEquations(ExpandableStatefulODE) -
Method in class org.apache.commons.math3.ode.JacobianMatrices
- Register the variational equations for the Jacobians matrices to the expandable set.
- regress() -
Method in class org.apache.commons.math3.stat.regression.MillerUpdatingRegression
- Conducts a regression on the data in the model, using all regressors.
- regress(int) -
Method in class org.apache.commons.math3.stat.regression.MillerUpdatingRegression
- Conducts a regression on the data in the model, using a subset of regressors.
- regress(int[]) -
Method in class org.apache.commons.math3.stat.regression.MillerUpdatingRegression
- Conducts a regression on the data in the model, using regressors in array
Calling this method will change the internal order of the regressors
and care is required in interpreting the hatmatrix.
- regress() -
Method in class org.apache.commons.math3.stat.regression.SimpleRegression
- Performs a regression on data present in buffers and outputs a RegressionResults object.
- regress(int[]) -
Method in class org.apache.commons.math3.stat.regression.SimpleRegression
- Performs a regression on data present in buffers including only regressors
indexed in variablesToInclude and outputs a RegressionResults object
- regress() -
Method in interface org.apache.commons.math3.stat.regression.UpdatingMultipleLinearRegression
- Performs a regression on data present in buffers and outputs a RegressionResults object
- regress(int[]) -
Method in interface org.apache.commons.math3.stat.regression.UpdatingMultipleLinearRegression
- Performs a regression on data present in buffers including only regressors
indexed in variablesToInclude and outputs a RegressionResults object
- RegressionResults - Class in org.apache.commons.math3.stat.regression
- Results of a Multiple Linear Regression model fit.
- RegressionResults(double[], double[][], boolean, long, int, double, double, double, boolean, boolean) -
Constructor for class org.apache.commons.math3.stat.regression.RegressionResults
- Constructor for Regression Results.
- RegulaFalsiSolver - Class in org.apache.commons.math3.analysis.solvers
- Implements the Regula Falsi or False position method for
root-finding (approximating a zero of a univariate real function).
- RegulaFalsiSolver() -
Constructor for class org.apache.commons.math3.analysis.solvers.RegulaFalsiSolver
- Construct a solver with default accuracy (1e-6).
- RegulaFalsiSolver(double) -
Constructor for class org.apache.commons.math3.analysis.solvers.RegulaFalsiSolver
- Construct a solver.
- RegulaFalsiSolver(double, double) -
Constructor for class org.apache.commons.math3.analysis.solvers.RegulaFalsiSolver
- Construct a solver.
- RegulaFalsiSolver(double, double, double) -
Constructor for class org.apache.commons.math3.analysis.solvers.RegulaFalsiSolver
- Construct a solver.
- regularizedBeta(double, double, double) -
Static method in class org.apache.commons.math3.special.Beta
- Returns the
regularized beta function I(x, a, b).
- regularizedBeta(double, double, double, double) -
Static method in class org.apache.commons.math3.special.Beta
- Returns the
regularized beta function I(x, a, b).
- regularizedBeta(double, double, double, int) -
Static method in class org.apache.commons.math3.special.Beta
- Returns the regularized beta function I(x, a, b).
- regularizedBeta(double, double, double, double, int) -
Static method in class org.apache.commons.math3.special.Beta
- Returns the regularized beta function I(x, a, b).
- regularizedGammaP(double, double) -
Static method in class org.apache.commons.math3.special.Gamma
- Returns the regularized gamma function P(a, x).
- regularizedGammaP(double, double, double, int) -
Static method in class org.apache.commons.math3.special.Gamma
- Returns the regularized gamma function P(a, x).
- regularizedGammaQ(double, double) -
Static method in class org.apache.commons.math3.special.Gamma
- Returns the regularized gamma function Q(a, x) = 1 - P(a, x).
- regularizedGammaQ(double, double, double, int) -
Static method in class org.apache.commons.math3.special.Gamma
- Returns the regularized gamma function Q(a, x) = 1 - P(a, x).
- reinitialize(double[], boolean, EquationsMapper, EquationsMapper[]) -
Method in class org.apache.commons.math3.ode.sampling.AbstractStepInterpolator
- Reinitialize the instance
- reinitialize(double[], boolean, EquationsMapper, EquationsMapper[]) -
Method in class org.apache.commons.math3.ode.sampling.NordsieckStepInterpolator
- Reinitialize the instance.
- reinitialize(double, double, double[], Array2DRowRealMatrix) -
Method in class org.apache.commons.math3.ode.sampling.NordsieckStepInterpolator
- Reinitialize the instance.
- reinitializeBegin(StepInterpolator) -
Method in class org.apache.commons.math3.ode.events.EventState
- Reinitialize the beginning of the step.
- Relationship - Enum in org.apache.commons.math3.optim.linear
- Types of relationships between two cells in a Solver
LinearConstraint. - Relationship - Enum in org.apache.commons.math3.optimization.linear
- Deprecated. As of 3.1 (to be removed in 4.0).
- remainder(double) -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- IEEE remainder operator.
- remainder(DerivativeStructure) -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- IEEE remainder operator.
- remainder(double[], int, double[], int, double[], int) -
Method in class org.apache.commons.math3.analysis.differentiation.DSCompiler
- Perform remainder of two derivative structures.
- remainder(Dfp) -
Method in class org.apache.commons.math3.dfp.Dfp
- Returns the IEEE remainder.
- remainder(double) -
Method in class org.apache.commons.math3.dfp.Dfp
- IEEE remainder operator.
- remainder(double) -
Method in interface org.apache.commons.math3.RealFieldElement
- IEEE remainder operator.
- remainder(T) -
Method in interface org.apache.commons.math3.RealFieldElement
- IEEE remainder operator.
- remainder(double) -
Method in class org.apache.commons.math3.util.Decimal64
- IEEE remainder operator.
- remainder(Decimal64) -
Method in class org.apache.commons.math3.util.Decimal64
- IEEE remainder operator.
- remove() -
Method in class org.apache.commons.math3.linear.OpenMapRealVector.OpenMapSparseIterator
- Deprecated.
- remove() -
Method in class org.apache.commons.math3.linear.RealVector.SparseEntryIterator
- Deprecated.
- remove() -
Method in class org.apache.commons.math3.util.MultidimensionalCounter.Iterator
-
- remove(int) -
Method in class org.apache.commons.math3.util.OpenIntToDoubleHashMap
- Remove the value associated with a key.
- remove(int) -
Method in class org.apache.commons.math3.util.OpenIntToFieldHashMap
- Remove the value associated with a key.
- REMOVED -
Static variable in class org.apache.commons.math3.util.OpenIntToDoubleHashMap
- Status indicator for removed table entries.
- REMOVED -
Static variable in class org.apache.commons.math3.util.OpenIntToFieldHashMap
- Status indicator for removed table entries.
- removeData(double, double) -
Method in class org.apache.commons.math3.stat.regression.SimpleRegression
- Removes the observation (x,y) from the regression data set.
- removeData(double[][]) -
Method in class org.apache.commons.math3.stat.regression.SimpleRegression
- Removes observations represented by the elements in
data.
- removeIterationListener(IterationListener) -
Method in class org.apache.commons.math3.util.IterationManager
- Removes the specified iteration listener from the list of listeners
currently attached to
this object.
- removeMostRecentValue() -
Method in class org.apache.commons.math3.stat.descriptive.DescriptiveStatistics
- Removes the most recent value from the dataset.
- removeTransformer(Class<?>) -
Method in class org.apache.commons.math3.util.TransformerMap
- Removes a Class to Transformer Mapping in the Map.
- replaceMostRecentValue(double) -
Method in class org.apache.commons.math3.stat.descriptive.DescriptiveStatistics
- Replaces the most recently stored value with the given value.
- replaceWorstPoint(PointValuePair, Comparator<PointValuePair>) -
Method in class org.apache.commons.math3.optim.nonlinear.scalar.noderiv.AbstractSimplex
- Replace the worst point of the simplex by a new point.
- replaceWorstPoint(PointValuePair, Comparator<PointValuePair>) -
Method in class org.apache.commons.math3.optimization.direct.AbstractSimplex
- Deprecated. Replace the worst point of the simplex by a new point.
- REPLAY_MODE -
Static variable in class org.apache.commons.math3.random.ValueServer
- Replay data from valuesFilePath.
- representableDelta(double, double) -
Static method in class org.apache.commons.math3.util.Precision
- Computes a number
delta close to originalDelta with
the property that
x + delta - x
is exactly machine-representable.
- rescale(double) -
Method in class org.apache.commons.math3.ode.sampling.NordsieckStepInterpolator
- Rescale the instance.
- reSeed(long) -
Method in class org.apache.commons.math3.random.EmpiricalDistribution
- Reseeds the random number generator used by
EmpiricalDistribution.getNextValue().
- reSeed(long) -
Method in class org.apache.commons.math3.random.RandomDataGenerator
- Reseeds the random number generator with the supplied seed.
- reSeed() -
Method in class org.apache.commons.math3.random.RandomDataGenerator
- Reseeds the random number generator with
System.currentTimeMillis() + System.identityHashCode(this)).
- reSeed(long) -
Method in class org.apache.commons.math3.random.RandomDataImpl
- Deprecated. Reseeds the random number generator with the supplied seed.
- reSeed() -
Method in class org.apache.commons.math3.random.RandomDataImpl
- Deprecated. Reseeds the random number generator with
System.currentTimeMillis() + System.identityHashCode(this)).
- reSeed(long) -
Method in class org.apache.commons.math3.random.ValueServer
- Reseeds the random data generator.
- reseedRandomGenerator(long) -
Method in class org.apache.commons.math3.distribution.AbstractIntegerDistribution
- Reseed the random generator used to generate samples.
- reseedRandomGenerator(long) -
Method in class org.apache.commons.math3.distribution.AbstractMultivariateRealDistribution
- Reseeds the random generator used to generate samples.
- reseedRandomGenerator(long) -
Method in class org.apache.commons.math3.distribution.AbstractRealDistribution
- Reseed the random generator used to generate samples.
- reseedRandomGenerator(long) -
Method in class org.apache.commons.math3.distribution.EnumeratedDistribution
- Reseed the random generator used to generate samples.
- reseedRandomGenerator(long) -
Method in interface org.apache.commons.math3.distribution.IntegerDistribution
- Reseed the random generator used to generate samples.
- reseedRandomGenerator(long) -
Method in class org.apache.commons.math3.distribution.MixtureMultivariateRealDistribution
- Reseeds the random generator used to generate samples.
- reseedRandomGenerator(long) -
Method in interface org.apache.commons.math3.distribution.MultivariateRealDistribution
- Reseeds the random generator used to generate samples.
- reseedRandomGenerator(long) -
Method in interface org.apache.commons.math3.distribution.RealDistribution
- Reseed the random generator used to generate samples.
- reseedRandomGenerator(long) -
Method in class org.apache.commons.math3.random.EmpiricalDistribution
- Reseed the random generator used to generate samples.
- reSeedSecure() -
Method in class org.apache.commons.math3.random.RandomDataGenerator
- Reseeds the secure random number generator with the current time in
milliseconds.
- reSeedSecure(long) -
Method in class org.apache.commons.math3.random.RandomDataGenerator
- Reseeds the secure random number generator with the supplied seed.
- reSeedSecure() -
Method in class org.apache.commons.math3.random.RandomDataImpl
- Deprecated. Reseeds the secure random number generator with the current time in
milliseconds.
- reSeedSecure(long) -
Method in class org.apache.commons.math3.random.RandomDataImpl
- Deprecated. Reseeds the secure random number generator with the supplied seed.
- reset(Vector3D, Vector3D) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.Line
- Reset the instance as if built from two points.
- reset(Vector3D, Vector3D) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.Plane
- Reset the instance as if built from a point and a normal.
- reset(Plane) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.Plane
- Reset the instance from another one.
- reset(Vector2D, Vector2D) -
Method in class org.apache.commons.math3.geometry.euclidean.twod.Line
- Reset the instance as if built from two points.
- reset(Vector2D, double) -
Method in class org.apache.commons.math3.geometry.euclidean.twod.Line
- Reset the instance as if built from a line and an angle.
- reset(double, double[]) -
Method in class org.apache.commons.math3.ode.events.EventState
- Let the event handler reset the state if it wants.
- resetCount() -
Method in class org.apache.commons.math3.util.Incrementor
- Resets the counter to 0.
- resetInternalState() -
Method in class org.apache.commons.math3.ode.nonstiff.AdaptiveStepsizeIntegrator
- Reset internal state to dummy values.
- resetIterationCount() -
Method in class org.apache.commons.math3.util.IterationManager
- Sets the iteration count to 0.
- resetOccurred -
Variable in class org.apache.commons.math3.ode.AbstractIntegrator
- Indicator that a state or derivative reset was triggered by some event.
- resetReplayFile() -
Method in class org.apache.commons.math3.random.ValueServer
- Resets REPLAY_MODE file pointer to the beginning of the
valuesFileURL.
- resetState(double, double[]) -
Method in class org.apache.commons.math3.ode.events.EventFilter
- Reset the state prior to continue the integration.
- resetState(double, double[]) -
Method in interface org.apache.commons.math3.ode.events.EventHandler
- Reset the state prior to continue the integration.
- ResizableDoubleArray - Class in org.apache.commons.math3.util
-
A variable length
DoubleArray implementation that automatically
handles expanding and contracting its internal storage array as elements
are added and removed. - ResizableDoubleArray() -
Constructor for class org.apache.commons.math3.util.ResizableDoubleArray
- Creates an instance with default properties.
- ResizableDoubleArray(int) -
Constructor for class org.apache.commons.math3.util.ResizableDoubleArray
- Creates an instance with the specified initial capacity.
- ResizableDoubleArray(double[]) -
Constructor for class org.apache.commons.math3.util.ResizableDoubleArray
- Creates an instance from an existing
double[] with the
initial capacity and numElements corresponding to the size of
the supplied double[] array.
- ResizableDoubleArray(int, float) -
Constructor for class org.apache.commons.math3.util.ResizableDoubleArray
- Deprecated. As of 3.1. Please use
ResizableDoubleArray.ResizableDoubleArray(int,double) instead.
- ResizableDoubleArray(int, double) -
Constructor for class org.apache.commons.math3.util.ResizableDoubleArray
- Creates an instance with the specified initial capacity
and expansion factor.
- ResizableDoubleArray(int, float, float) -
Constructor for class org.apache.commons.math3.util.ResizableDoubleArray
- Deprecated. As of 3.1. Please use
ResizableDoubleArray.ResizableDoubleArray(int,double,double) instead.
- ResizableDoubleArray(int, double, double) -
Constructor for class org.apache.commons.math3.util.ResizableDoubleArray
- Creates an instance with the specified initial capacity,
expansion factor, and contraction criteria.
- ResizableDoubleArray(int, float, float, int) -
Constructor for class org.apache.commons.math3.util.ResizableDoubleArray
- Deprecated. As of 3.1. Please use
ResizableDoubleArray.ResizableDoubleArray(int,double,double,ExpansionMode,double[])
instead.
- ResizableDoubleArray(int, double, double, ResizableDoubleArray.ExpansionMode, double...) -
Constructor for class org.apache.commons.math3.util.ResizableDoubleArray
- Creates an instance with the specified properties.
- ResizableDoubleArray(ResizableDoubleArray) -
Constructor for class org.apache.commons.math3.util.ResizableDoubleArray
- Copy constructor.
- ResizableDoubleArray.ExpansionMode - Enum in org.apache.commons.math3.util
- Specification of expansion algorithm.
- restrictToNonNegative() -
Method in class org.apache.commons.math3.optimization.linear.AbstractLinearOptimizer
- Deprecated.
- reunite(SubHyperplane<S>) -
Method in class org.apache.commons.math3.geometry.partitioning.AbstractSubHyperplane
- Compute the union of the instance and another sub-hyperplane.
- reunite(SubHyperplane<S>) -
Method in interface org.apache.commons.math3.geometry.partitioning.SubHyperplane
- Compute the union of the instance and another sub-hyperplane.
- revert() -
Method in class org.apache.commons.math3.geometry.euclidean.threed.FieldRotation
- Revert a rotation.
- revert() -
Method in class org.apache.commons.math3.geometry.euclidean.threed.Line
- Get a line with reversed direction.
- revert() -
Method in class org.apache.commons.math3.geometry.euclidean.threed.Rotation
- Revert a rotation.
- revertSelf() -
Method in class org.apache.commons.math3.geometry.euclidean.oned.OrientedPoint
- Revert the instance.
- revertSelf() -
Method in class org.apache.commons.math3.geometry.euclidean.threed.Plane
- Revert the plane.
- revertSelf() -
Method in class org.apache.commons.math3.geometry.euclidean.twod.Line
- Revert the instance.
- RiddersSolver - Class in org.apache.commons.math3.analysis.solvers
- Implements the
Ridders' Method for root finding of real univariate functions.
- RiddersSolver() -
Constructor for class org.apache.commons.math3.analysis.solvers.RiddersSolver
- Construct a solver with default accuracy (1e-6).
- RiddersSolver(double) -
Constructor for class org.apache.commons.math3.analysis.solvers.RiddersSolver
- Construct a solver.
- RiddersSolver(double, double) -
Constructor for class org.apache.commons.math3.analysis.solvers.RiddersSolver
- Construct a solver.
- rint() -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- Get the whole number that is the nearest to the instance, or the even one if x is exactly half way between two integers.
- Rint - Class in org.apache.commons.math3.analysis.function
rint function.- Rint() -
Constructor for class org.apache.commons.math3.analysis.function.Rint
-
- rint() -
Method in class org.apache.commons.math3.dfp.Dfp
- Round to nearest integer using the round-half-even method.
- rint() -
Method in interface org.apache.commons.math3.RealFieldElement
- Get the whole number that is the nearest to the instance, or the even one if x is exactly half way between two integers.
- rint() -
Method in class org.apache.commons.math3.util.Decimal64
- Get the whole number that is the nearest to the instance, or the even one if x is exactly half way between two integers.
- rint(double) -
Static method in class org.apache.commons.math3.util.FastMath
- Get the whole number that is the nearest to x, or the even one if x is exactly half way between two integers.
- ROMBERG_MAX_ITERATIONS_COUNT -
Static variable in class org.apache.commons.math3.analysis.integration.RombergIntegrator
- Maximal number of iterations for Romberg.
- RombergIntegrator - Class in org.apache.commons.math3.analysis.integration
- Implements the
Romberg Algorithm for integration of real univariate functions.
- RombergIntegrator(double, double, int, int) -
Constructor for class org.apache.commons.math3.analysis.integration.RombergIntegrator
- Build a Romberg integrator with given accuracies and iterations counts.
- RombergIntegrator(int, int) -
Constructor for class org.apache.commons.math3.analysis.integration.RombergIntegrator
- Build a Romberg integrator with given iteration counts.
- RombergIntegrator() -
Constructor for class org.apache.commons.math3.analysis.integration.RombergIntegrator
- Construct a Romberg integrator with default settings
(max iteration count set to
RombergIntegrator.ROMBERG_MAX_ITERATIONS_COUNT)
- rootLogLikelihoodRatio(long, long, long, long) -
Method in class org.apache.commons.math3.stat.inference.GTest
- Calculates the root log-likelihood ratio for 2 state Datasets.
- rootLogLikelihoodRatio(long, long, long, long) -
Static method in class org.apache.commons.math3.stat.inference.TestUtils
-
- rootN(int) -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- Nth root.
- rootN(double[], int, int, double[], int) -
Method in class org.apache.commons.math3.analysis.differentiation.DSCompiler
- Compute nth root of a derivative structure.
- rootN(int) -
Method in class org.apache.commons.math3.dfp.Dfp
- Nth root.
- rootN(int) -
Method in interface org.apache.commons.math3.RealFieldElement
- Nth root.
- rootN(int) -
Method in class org.apache.commons.math3.util.Decimal64
- Nth root.
- RootsOfUnity - Class in org.apache.commons.math3.complex
- A helper class for the computation and caching of the
n-th roots of
unity. - RootsOfUnity() -
Constructor for class org.apache.commons.math3.complex.RootsOfUnity
- Build an engine for computing the
n-th roots of unity.
- rotate(Vector3D, Rotation) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.Plane
- Rotate the plane around the specified point.
- rotate(Vector3D, Rotation) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.PolyhedronsSet
- Rotate the region around the specified point.
- Rotation - Class in org.apache.commons.math3.geometry.euclidean.threed
- This class implements rotations in a three-dimensional space.
- Rotation(double, double, double, double, boolean) -
Constructor for class org.apache.commons.math3.geometry.euclidean.threed.Rotation
- Build a rotation from the quaternion coordinates.
- Rotation(Vector3D, double) -
Constructor for class org.apache.commons.math3.geometry.euclidean.threed.Rotation
- Build a rotation from an axis and an angle.
- Rotation(double[][], double) -
Constructor for class org.apache.commons.math3.geometry.euclidean.threed.Rotation
- Build a rotation from a 3X3 matrix.
- Rotation(Vector3D, Vector3D, Vector3D, Vector3D) -
Constructor for class org.apache.commons.math3.geometry.euclidean.threed.Rotation
- Build the rotation that transforms a pair of vector into another pair.
- Rotation(Vector3D, Vector3D) -
Constructor for class org.apache.commons.math3.geometry.euclidean.threed.Rotation
- Build one of the rotations that transform one vector into another one.
- Rotation(RotationOrder, double, double, double) -
Constructor for class org.apache.commons.math3.geometry.euclidean.threed.Rotation
- Build a rotation from three Cardan or Euler elementary rotations.
- RotationOrder - Class in org.apache.commons.math3.geometry.euclidean.threed
- This class is a utility representing a rotation order specification
for Cardan or Euler angles specification.
- round() -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- Get the closest long to instance value.
- round(int) -
Method in class org.apache.commons.math3.dfp.Dfp
- Round this given the next digit n using the current rounding mode.
- round() -
Method in class org.apache.commons.math3.dfp.Dfp
- Get the closest long to instance value.
- round(int) -
Method in class org.apache.commons.math3.dfp.DfpDec
- Round this given the next digit n using the current rounding mode.
- round() -
Method in interface org.apache.commons.math3.RealFieldElement
- Get the closest long to instance value.
- round() -
Method in class org.apache.commons.math3.util.Decimal64
- Get the closest long to instance value.
- round(double) -
Static method in class org.apache.commons.math3.util.FastMath
- Get the closest long to x.
- round(float) -
Static method in class org.apache.commons.math3.util.FastMath
- Get the closest int to x.
- round(double, int) -
Static method in class org.apache.commons.math3.util.Precision
- Rounds the given value to the specified number of decimal places.
- round(double, int, int) -
Static method in class org.apache.commons.math3.util.Precision
- Rounds the given value to the specified number of decimal places.
- round(float, int) -
Static method in class org.apache.commons.math3.util.Precision
- Rounds the given value to the specified number of decimal places.
- round(float, int, int) -
Static method in class org.apache.commons.math3.util.Precision
- Rounds the given value to the specified number of decimal places.
- rows -
Variable in class org.apache.commons.math3.optimization.general.AbstractLeastSquaresOptimizer
- Deprecated. As of 3.1.
- RRQRDecomposition - Class in org.apache.commons.math3.linear
- Calculates the rank-revealing QR-decomposition of a matrix, with column pivoting.
- RRQRDecomposition(RealMatrix) -
Constructor for class org.apache.commons.math3.linear.RRQRDecomposition
- Calculates the QR-decomposition of the given matrix.
- RRQRDecomposition(RealMatrix, double) -
Constructor for class org.apache.commons.math3.linear.RRQRDecomposition
- Calculates the QR-decomposition of the given matrix.
- RungeKuttaIntegrator - Class in org.apache.commons.math3.ode.nonstiff
- This class implements the common part of all fixed step Runge-Kutta
integrators for Ordinary Differential Equations.
- RungeKuttaIntegrator(String, double[], double[][], double[], RungeKuttaStepInterpolator, double) -
Constructor for class org.apache.commons.math3.ode.nonstiff.RungeKuttaIntegrator
- Simple constructor.
1 / SAFE_MIN does not overflow.
d to each entry of this.
d to each entry of this.
d to each entry of this.
d.
this by
d.
d.
this by
d.
d.
this by
d.
SecondMoment identical
to the original
biasCorrected
property and default (Downside) varianceDirection property.
biasCorrected
property and default (Downside) varianceDirection property.
Direction property
and default (true) biasCorrected property
isBiasCorrected
property and the specified Direction property.
SemiVariance identical
to the original
RealMatrix.
RealVector.
ListPopulation.addChromosomes(Collection) instead
column
as a column matrix.
column of this matrix to the entries
of the specified array.
column
as a column matrix.
column of this matrix to the entries
of the specified array.
column
as a column matrix.
column of this matrix to the entries
of the specified array.
column
as a column matrix.
column of this matrix to the entries
of the specified column matrix.
column
as a column matrix.
column of this matrix to the entries
of the specified column matrix.
column
as a column matrix.
column of this matrix to the entries
of the specified column matrix.
column
as a vector.
column of this matrix to the entries
of the specified vector.
column
as a vector.
column of this matrix to the entries
of the specified vector.
column
as a vector.
column of this matrix to the entries
of the specified vector.
ResizableDoubleArray.setExpansionMode(ExpansionMode) instead.
mean used in data generation.
DescriptiveStatistics.getPercentile(double).
index.
index.
row
as a row matrix.
row of this matrix to the entries
of the specified array.
row
as a row matrix.
row of this matrix to the entries
of the specified array.
row
as a row matrix.
row of this matrix to the entries
of the specified array.
row
as a row matrix.
row of this matrix to the entries of
the specified row matrix.
row
as a row matrix.
row
as a row matrix.
row of this matrix to the entries of
the specified row matrix.
row
as a row matrix.
row
as a row matrix.
row of this matrix to the entries of
the specified row matrix.
row
as a vector.
row of this matrix to the entries of
the specified vector.
row
as a vector.
row of this matrix to the entries of
the specified vector.
row
as a vector.
row of this matrix to the entries of
the specified vector.
int seed.
int array seed.
long seed.
int seed.
int array seed.
long seed.
int seed.
long seed.
int array seed.
int seed.
int array seed.
int seed.
int array seed.
long seed.
int seed.
int array seed.
long seed.
int seed.
int array seed.
long seed.
standard deviation used in ValueServer.GAUSSIAN_MODE.
BaseAbstractMultivariateOptimizer.optimize(int,MultivariateFunction,GoalType,OptimizationData[])
method.
(row, column) using data in the
input subMatrix array.
row, column using data in the
input subMatrix array.
(row, column) using data in the
input subMatrix array.
row, column using data in the
input subMatrix array.
(row, column) using data in the
input subMatrix array.
row, column using data in the
input subMatrix array.
(row, column) using data in the
input subMatrix array.
row, column using data in the
input subMatrix array.
input parsed by this base
class.
input parsed by this base
class.
values file URL using a string
URL representation.
values file URL.
Ps(x)
whose values at point x will be the same as the those from the
original polynomial P(x) when computed at x + shift.
short.
hyperplane of a space.signum function.ConvergenceChecker interface using
only point coordinates.AbstractConvergenceChecker.AbstractConvergenceChecker()
ConvergenceChecker interface
that uses only objective function values.AbstractConvergenceChecker.AbstractConvergenceChecker()
ConvergenceChecker interface using
only objective function values.AbstractConvergenceChecker.AbstractConvergenceChecker()
ConvergenceChecker interface using
only objective function values.AbstractConvergenceChecker.AbstractConvergenceChecker()
SimpleValueChecker.SimpleValueChecker()
sinc(x) = 1 if x = 0,
sin(x) / x otherwise.- Sinc() -
Constructor for class org.apache.commons.math3.analysis.function.Sinc
- The sinc function,
sin(x) / x.
- Sinc(boolean) -
Constructor for class org.apache.commons.math3.analysis.function.Sinc
- Instantiates the sinc function.
- SingularMatrixException - Exception in org.apache.commons.math3.linear
- Exception to be thrown when a non-singular matrix is expected.
- SingularMatrixException() -
Constructor for exception org.apache.commons.math3.linear.SingularMatrixException
- Construct an exception.
- SingularOperatorException - Exception in org.apache.commons.math3.linear
- Exception to be thrown when trying to invert a singular operator.
- SingularOperatorException() -
Constructor for exception org.apache.commons.math3.linear.SingularOperatorException
- Creates a new instance of this class.
- SingularValueDecomposition - Class in org.apache.commons.math3.linear
- Calculates the compact Singular Value Decomposition of a matrix.
- SingularValueDecomposition(RealMatrix) -
Constructor for class org.apache.commons.math3.linear.SingularValueDecomposition
- Calculates the compact Singular Value Decomposition of the given matrix.
- sinh() -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- Hyperbolic sine operation.
- sinh(double[], int, double[], int) -
Method in class org.apache.commons.math3.analysis.differentiation.DSCompiler
- Compute hyperbolic sine of a derivative structure.
- Sinh - Class in org.apache.commons.math3.analysis.function
- Hyperbolic sine function.
- Sinh() -
Constructor for class org.apache.commons.math3.analysis.function.Sinh
-
- sinh() -
Method in class org.apache.commons.math3.complex.Complex
- Compute the
hyperbolic sine of this complex number.
- sinh() -
Method in class org.apache.commons.math3.dfp.Dfp
- Hyperbolic sine operation.
- sinh() -
Method in interface org.apache.commons.math3.RealFieldElement
- Hyperbolic sine operation.
- sinh() -
Method in class org.apache.commons.math3.util.Decimal64
- Hyperbolic sine operation.
- sinh(double) -
Static method in class org.apache.commons.math3.util.FastMath
- Compute the hyperbolic sine of a number.
- sinInternal(Dfp[]) -
Static method in class org.apache.commons.math3.dfp.DfpMath
- Computes sin(a) Used when 0 < a < pi/4.
- size() -
Method in class org.apache.commons.math3.geometry.partitioning.utilities.AVLTree
- Get the number of elements of the tree.
- size() -
Method in class org.apache.commons.math3.util.OpenIntToDoubleHashMap
- Get the number of elements stored in the map.
- size() -
Method in class org.apache.commons.math3.util.OpenIntToFieldHashMap
- Get the number of elements stored in the map.
- Skewness - Class in org.apache.commons.math3.stat.descriptive.moment
- Computes the skewness of the available values.
- Skewness() -
Constructor for class org.apache.commons.math3.stat.descriptive.moment.Skewness
- Constructs a Skewness
- Skewness(ThirdMoment) -
Constructor for class org.apache.commons.math3.stat.descriptive.moment.Skewness
- Constructs a Skewness with an external moment
- Skewness(Skewness) -
Constructor for class org.apache.commons.math3.stat.descriptive.moment.Skewness
- Copy constructor, creates a new
Skewness identical
to the original
- smooth(double[], double[], double[]) -
Method in class org.apache.commons.math3.analysis.interpolation.LoessInterpolator
- Compute a weighted loess fit on the data at the original abscissae.
- smooth(double[], double[]) -
Method in class org.apache.commons.math3.analysis.interpolation.LoessInterpolator
- Compute a loess fit on the data at the original abscissae.
- SmoothingPolynomialBicubicSplineInterpolator - Class in org.apache.commons.math3.analysis.interpolation
- Generates a bicubic interpolation function.
- SmoothingPolynomialBicubicSplineInterpolator() -
Constructor for class org.apache.commons.math3.analysis.interpolation.SmoothingPolynomialBicubicSplineInterpolator
- Default constructor.
- SmoothingPolynomialBicubicSplineInterpolator(int) -
Constructor for class org.apache.commons.math3.analysis.interpolation.SmoothingPolynomialBicubicSplineInterpolator
-
- SmoothingPolynomialBicubicSplineInterpolator(int, int) -
Constructor for class org.apache.commons.math3.analysis.interpolation.SmoothingPolynomialBicubicSplineInterpolator
-
- SNAN -
Static variable in class org.apache.commons.math3.dfp.Dfp
- Indicator value for signaling NaN.
- solve(int, FUNC, double, double, double) -
Method in class org.apache.commons.math3.analysis.solvers.BaseAbstractUnivariateSolver
- Solve for a zero in the given interval, start at
startValue.
- solve(int, FUNC, double, double) -
Method in class org.apache.commons.math3.analysis.solvers.BaseAbstractUnivariateSolver
- Solve for a zero root in the given interval.
- solve(int, FUNC, double) -
Method in class org.apache.commons.math3.analysis.solvers.BaseAbstractUnivariateSolver
- Solve for a zero in the vicinity of
startValue.
- solve(int, UnivariateFunction, double, double, AllowedSolution) -
Method in class org.apache.commons.math3.analysis.solvers.BaseSecantSolver
- Solve for a zero in the given interval.
- solve(int, UnivariateFunction, double, double, double, AllowedSolution) -
Method in class org.apache.commons.math3.analysis.solvers.BaseSecantSolver
- Solve for a zero in the given interval, start at
startValue.
- solve(int, UnivariateFunction, double, double, double) -
Method in class org.apache.commons.math3.analysis.solvers.BaseSecantSolver
- Solve for a zero in the given interval, start at
startValue.
- solve(int, FUNC, double, double) -
Method in interface org.apache.commons.math3.analysis.solvers.BaseUnivariateSolver
- Solve for a zero root in the given interval.
- solve(int, FUNC, double, double, double) -
Method in interface org.apache.commons.math3.analysis.solvers.BaseUnivariateSolver
- Solve for a zero in the given interval, start at
startValue.
- solve(int, FUNC, double) -
Method in interface org.apache.commons.math3.analysis.solvers.BaseUnivariateSolver
- Solve for a zero in the vicinity of
startValue.
- solve(int, FUNC, double, double, AllowedSolution) -
Method in interface org.apache.commons.math3.analysis.solvers.BracketedUnivariateSolver
- Solve for a zero in the given interval.
- solve(int, FUNC, double, double, double, AllowedSolution) -
Method in interface org.apache.commons.math3.analysis.solvers.BracketedUnivariateSolver
- Solve for a zero in the given interval, start at
startValue.
- solve(int, UnivariateFunction, double, double, AllowedSolution) -
Method in class org.apache.commons.math3.analysis.solvers.BracketingNthOrderBrentSolver
- Solve for a zero in the given interval.
- solve(int, UnivariateFunction, double, double, double, AllowedSolution) -
Method in class org.apache.commons.math3.analysis.solvers.BracketingNthOrderBrentSolver
- Solve for a zero in the given interval, start at
startValue.
- solve(int, UnivariateDifferentiableFunction, double, double) -
Method in class org.apache.commons.math3.analysis.solvers.NewtonRaphsonSolver
- Find a zero near the midpoint of
min and max.
- solve(int, DifferentiableUnivariateFunction, double, double) -
Method in class org.apache.commons.math3.analysis.solvers.NewtonSolver
- Deprecated. Find a zero near the midpoint of
min and max.
- solve(UnivariateFunction, double, double) -
Static method in class org.apache.commons.math3.analysis.solvers.UnivariateSolverUtils
- Convenience method to find a zero of a univariate real function.
- solve(UnivariateFunction, double, double, double) -
Static method in class org.apache.commons.math3.analysis.solvers.UnivariateSolverUtils
- Convenience method to find a zero of a univariate real function.
- solve(int, UnivariateDfpFunction, Dfp, Dfp, AllowedSolution) -
Method in class org.apache.commons.math3.dfp.BracketingNthOrderBrentSolverDFP
- Solve for a zero in the given interval.
- solve(int, UnivariateDfpFunction, Dfp, Dfp, Dfp, AllowedSolution) -
Method in class org.apache.commons.math3.dfp.BracketingNthOrderBrentSolverDFP
- Solve for a zero in the given interval, start at
startValue.
- solve(RealVector) -
Method in interface org.apache.commons.math3.linear.DecompositionSolver
- Solve the linear equation A × X = B for matrices A.
- solve(RealMatrix) -
Method in interface org.apache.commons.math3.linear.DecompositionSolver
- Solve the linear equation A × X = B for matrices A.
- solve(FieldVector<T>) -
Method in interface org.apache.commons.math3.linear.FieldDecompositionSolver
- Solve the linear equation A × X = B for matrices A.
- solve(FieldMatrix<T>) -
Method in interface org.apache.commons.math3.linear.FieldDecompositionSolver
- Solve the linear equation A × X = B for matrices A.
- solve(RealLinearOperator, RealVector) -
Method in class org.apache.commons.math3.linear.IterativeLinearSolver
- Returns an estimate of the solution to the linear system A · x =
b.
- solve(RealLinearOperator, RealVector, RealVector) -
Method in class org.apache.commons.math3.linear.IterativeLinearSolver
- Returns an estimate of the solution to the linear system A · x =
b.
- solve(RealLinearOperator, RealLinearOperator, RealVector, RealVector) -
Method in class org.apache.commons.math3.linear.PreconditionedIterativeLinearSolver
- Returns an estimate of the solution to the linear system A · x =
b.
- solve(RealLinearOperator, RealVector) -
Method in class org.apache.commons.math3.linear.PreconditionedIterativeLinearSolver
- Returns an estimate of the solution to the linear system A · x =
b.
- solve(RealLinearOperator, RealVector, RealVector) -
Method in class org.apache.commons.math3.linear.PreconditionedIterativeLinearSolver
- Returns an estimate of the solution to the linear system A · x =
b.
- solve(RealLinearOperator, RealLinearOperator, RealVector) -
Method in class org.apache.commons.math3.linear.PreconditionedIterativeLinearSolver
- Returns an estimate of the solution to the linear system A · x =
b.
- solve(RealLinearOperator, RealLinearOperator, RealVector) -
Method in class org.apache.commons.math3.linear.SymmLQ
- Returns an estimate of the solution to the linear system A · x =
b.
- solve(RealLinearOperator, RealLinearOperator, RealVector, boolean, double) -
Method in class org.apache.commons.math3.linear.SymmLQ
- Returns an estimate of the solution to the linear system (A - shift
· I) · x = b.
- solve(RealLinearOperator, RealLinearOperator, RealVector, RealVector) -
Method in class org.apache.commons.math3.linear.SymmLQ
- Returns an estimate of the solution to the linear system A · x =
b.
- solve(RealLinearOperator, RealVector) -
Method in class org.apache.commons.math3.linear.SymmLQ
- Returns an estimate of the solution to the linear system A · x =
b.
- solve(RealLinearOperator, RealVector, boolean, double) -
Method in class org.apache.commons.math3.linear.SymmLQ
- Returns the solution to the system (A - shift · I) · x = b.
- solve(RealLinearOperator, RealVector, RealVector) -
Method in class org.apache.commons.math3.linear.SymmLQ
- Returns an estimate of the solution to the linear system A · x =
b.
- solveAllComplex(double[], double) -
Method in class org.apache.commons.math3.analysis.solvers.LaguerreSolver
- Find all complex roots for the polynomial with the given
coefficients, starting from the given initial value.
- solveComplex(double[], double) -
Method in class org.apache.commons.math3.analysis.solvers.LaguerreSolver
- Find a complex root for the polynomial with the given coefficients,
starting from the given initial value.
- solveInPlace(RealLinearOperator, RealLinearOperator, RealVector, RealVector) -
Method in class org.apache.commons.math3.linear.ConjugateGradient
- Returns an estimate of the solution to the linear system A · x =
b.
- solveInPlace(RealLinearOperator, RealVector, RealVector) -
Method in class org.apache.commons.math3.linear.IterativeLinearSolver
- Returns an estimate of the solution to the linear system A · x =
b.
- solveInPlace(RealLinearOperator, RealLinearOperator, RealVector, RealVector) -
Method in class org.apache.commons.math3.linear.PreconditionedIterativeLinearSolver
- Returns an estimate of the solution to the linear system A · x =
b.
- solveInPlace(RealLinearOperator, RealVector, RealVector) -
Method in class org.apache.commons.math3.linear.PreconditionedIterativeLinearSolver
- Returns an estimate of the solution to the linear system A · x =
b.
- solveInPlace(RealLinearOperator, RealLinearOperator, RealVector, RealVector) -
Method in class org.apache.commons.math3.linear.SymmLQ
- Returns an estimate of the solution to the linear system A · x =
b.
- solveInPlace(RealLinearOperator, RealLinearOperator, RealVector, RealVector, boolean, double) -
Method in class org.apache.commons.math3.linear.SymmLQ
- Returns an estimate of the solution to the linear system (A - shift
· I) · x = b.
- solveInPlace(RealLinearOperator, RealVector, RealVector) -
Method in class org.apache.commons.math3.linear.SymmLQ
- Returns an estimate of the solution to the linear system A · x =
b.
- solveInverseCumulativeProbability(double, int, int) -
Method in class org.apache.commons.math3.distribution.AbstractIntegerDistribution
- This is a utility function used by
AbstractIntegerDistribution.inverseCumulativeProbability(double).
- solveLowerTriangularSystem(RealMatrix, RealVector) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Solve a system of composed of a Lower Triangular Matrix
RealMatrix.
- solvePhase1(SimplexTableau) -
Method in class org.apache.commons.math3.optim.linear.SimplexSolver
- Solves Phase 1 of the Simplex method.
- solvePhase1(SimplexTableau) -
Method in class org.apache.commons.math3.optimization.linear.SimplexSolver
- Deprecated. Solves Phase 1 of the Simplex method.
- SOLVER_DEFAULT_ABSOLUTE_ACCURACY -
Static variable in class org.apache.commons.math3.distribution.AbstractRealDistribution
- Default accuracy.
- solveUpperTriangularSystem(RealMatrix, RealVector) -
Static method in class org.apache.commons.math3.linear.MatrixUtils
- Solver a system composed of an Upper Triangular Matrix
RealMatrix.
- sortInPlace(double[], double[]...) -
Static method in class org.apache.commons.math3.util.MathArrays
- Sort an array in ascending order in place and perform the same reordering
of entries on other arrays.
- sortInPlace(double[], MathArrays.OrderDirection, double[]...) -
Static method in class org.apache.commons.math3.util.MathArrays
- Sort an array in place and perform the same reordering of entries on
other arrays.
- Space - Interface in org.apache.commons.math3.geometry
- This interface represents a generic space, with affine and vectorial counterparts.
- SparseFieldMatrix<T extends FieldElement<T>> - Class in org.apache.commons.math3.linear
- Deprecated. As of version 3.1, this class is deprecated, for reasons exposed
in this JIRA
ticket. This
class will be removed in version 4.0.
- SparseFieldMatrix(Field<T>) -
Constructor for class org.apache.commons.math3.linear.SparseFieldMatrix
- Deprecated. Create a matrix with no data.
- SparseFieldMatrix(Field<T>, int, int) -
Constructor for class org.apache.commons.math3.linear.SparseFieldMatrix
- Deprecated. Create a new SparseFieldMatrix
with the supplied row and column
dimensions.
- SparseFieldMatrix(SparseFieldMatrix<T>) -
Constructor for class org.apache.commons.math3.linear.SparseFieldMatrix
- Deprecated. Copy constructor.
- SparseFieldMatrix(FieldMatrix<T>) -
Constructor for class org.apache.commons.math3.linear.SparseFieldMatrix
- Deprecated. Generic copy constructor.
- SparseFieldVector<T extends FieldElement<T>> - Class in org.apache.commons.math3.linear
- Deprecated. As of version 3.1, this class is deprecated, for reasons exposed
in this JIRA
ticket. This
class will be removed in version 4.0.
- SparseFieldVector(Field<T>) -
Constructor for class org.apache.commons.math3.linear.SparseFieldVector
- Deprecated. Build a 0-length vector.
- SparseFieldVector(Field<T>, int) -
Constructor for class org.apache.commons.math3.linear.SparseFieldVector
- Deprecated. Construct a vector of zeroes.
- SparseFieldVector(SparseFieldVector<T>, int) -
Constructor for class org.apache.commons.math3.linear.SparseFieldVector
- Deprecated. Build a resized vector, for use with append.
- SparseFieldVector(Field<T>, int, int) -
Constructor for class org.apache.commons.math3.linear.SparseFieldVector
- Deprecated. Build a vector with known the sparseness (for advanced use only).
- SparseFieldVector(Field<T>, T[]) -
Constructor for class org.apache.commons.math3.linear.SparseFieldVector
- Deprecated. Create from a Field array.
- SparseFieldVector(SparseFieldVector<T>) -
Constructor for class org.apache.commons.math3.linear.SparseFieldVector
- Deprecated. Copy constructor.
- sparseIterator() -
Method in class org.apache.commons.math3.linear.OpenMapRealVector
- Deprecated. Create a sparse iterator over the vector, which may omit some entries.
- sparseIterator() -
Method in class org.apache.commons.math3.linear.RealVector
- Deprecated. As of 3.1, this method is deprecated, because its interface
is too confusing (see
JIRA MATH-875).
This method will be completely removed in 4.0.
- SparseRealMatrix - Interface in org.apache.commons.math3.linear
- Deprecated. As of version 3.1, this class is deprecated, for reasons exposed
in this JIRA
ticket. This
class will be removed in version 4.0.
- SparseRealVector - Class in org.apache.commons.math3.linear
- Deprecated. As of version 3.1, this class is deprecated, for reasons exposed
in this JIRA
ticket. This
class will be removed in version 4.0.
- SparseRealVector() -
Constructor for class org.apache.commons.math3.linear.SparseRealVector
- Deprecated.
- SpearmansCorrelation - Class in org.apache.commons.math3.stat.correlation
- Spearman's rank correlation.
- SpearmansCorrelation() -
Constructor for class org.apache.commons.math3.stat.correlation.SpearmansCorrelation
- Create a SpearmansCorrelation without data.
- SpearmansCorrelation(RankingAlgorithm) -
Constructor for class org.apache.commons.math3.stat.correlation.SpearmansCorrelation
- Create a SpearmansCorrelation with the given ranking algorithm.
- SpearmansCorrelation(RealMatrix) -
Constructor for class org.apache.commons.math3.stat.correlation.SpearmansCorrelation
- Create a SpearmansCorrelation from the given data matrix.
- SpearmansCorrelation(RealMatrix, RankingAlgorithm) -
Constructor for class org.apache.commons.math3.stat.correlation.SpearmansCorrelation
- Create a SpearmansCorrelation with the given input data matrix
and ranking algorithm.
- SphericalCoordinates - Class in org.apache.commons.math3.geometry.euclidean.threed
- This class provides conversions related to spherical coordinates.
- SphericalCoordinates(Vector3D) -
Constructor for class org.apache.commons.math3.geometry.euclidean.threed.SphericalCoordinates
- Build a spherical coordinates transformer from Cartesian coordinates.
- SphericalCoordinates(double, double, double) -
Constructor for class org.apache.commons.math3.geometry.euclidean.threed.SphericalCoordinates
- Build a spherical coordinates transformer from spherical coordinates.
- SplineInterpolator - Class in org.apache.commons.math3.analysis.interpolation
- Computes a natural (also known as "free", "unclamped") cubic spline interpolation for the data set.
- SplineInterpolator() -
Constructor for class org.apache.commons.math3.analysis.interpolation.SplineInterpolator
-
- split(DfpField, String) -
Static method in class org.apache.commons.math3.dfp.DfpMath
- Breaks a string representation up into two dfp's.
- split(Dfp) -
Static method in class org.apache.commons.math3.dfp.DfpMath
- Splits a
Dfp into 2 Dfp's such that their sum is equal to the input Dfp.
- split(Hyperplane<Euclidean1D>) -
Method in class org.apache.commons.math3.geometry.euclidean.oned.SubOrientedPoint
- Split the instance in two parts by an hyperplane.
- split(Hyperplane<Euclidean3D>) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.SubPlane
- Split the instance in two parts by an hyperplane.
- split(Hyperplane<Euclidean2D>) -
Method in class org.apache.commons.math3.geometry.euclidean.twod.SubLine
- Split the instance in two parts by an hyperplane.
- split(Hyperplane<S>) -
Method in class org.apache.commons.math3.geometry.partitioning.AbstractSubHyperplane
- Split the instance in two parts by an hyperplane.
- split(SubHyperplane<S>) -
Method in class org.apache.commons.math3.geometry.partitioning.BSPTree
- Split a BSP tree by an external sub-hyperplane.
- split(Hyperplane<S>) -
Method in interface org.apache.commons.math3.geometry.partitioning.SubHyperplane
- Split the instance in two parts by an hyperplane.
- splitDiv(Dfp[], Dfp[]) -
Static method in class org.apache.commons.math3.dfp.DfpMath
- Divide two numbers that are split in to two pieces that are meant to be added together.
- splitMult(Dfp[], Dfp[]) -
Static method in class org.apache.commons.math3.dfp.DfpMath
- Multiply two numbers that are split in to two pieces that are
meant to be added together.
- splitPow(Dfp[], int) -
Static method in class org.apache.commons.math3.dfp.DfpMath
- Raise a split base to the a power.
- sqrt() -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- Square root.
- Sqrt - Class in org.apache.commons.math3.analysis.function
- Square-root function.
- Sqrt() -
Constructor for class org.apache.commons.math3.analysis.function.Sqrt
-
- sqrt() -
Method in class org.apache.commons.math3.complex.Complex
- Compute the
square root of this complex number.
- sqrt() -
Method in class org.apache.commons.math3.dfp.Dfp
- Compute the square root.
- sqrt() -
Method in class org.apache.commons.math3.linear.JacobiPreconditioner
- Returns the square root of
this diagonal operator.
- sqrt() -
Method in interface org.apache.commons.math3.RealFieldElement
- Square root.
- sqrt() -
Method in class org.apache.commons.math3.util.Decimal64
- Square root.
- sqrt(double) -
Static method in class org.apache.commons.math3.util.FastMath
- Compute the square root of a number.
- sqrt1z() -
Method in class org.apache.commons.math3.complex.Complex
- Compute the
square root of
1 - this2 for this complex
number.
- StableRandomGenerator - Class in org.apache.commons.math3.random
- This class provides a stable normalized random generator.
- StableRandomGenerator(RandomGenerator, double, double) -
Constructor for class org.apache.commons.math3.random.StableRandomGenerator
- Create a new generator.
- StandardDeviation - Class in org.apache.commons.math3.stat.descriptive.moment
- Computes the sample standard deviation.
- StandardDeviation() -
Constructor for class org.apache.commons.math3.stat.descriptive.moment.StandardDeviation
- Constructs a StandardDeviation.
- StandardDeviation(SecondMoment) -
Constructor for class org.apache.commons.math3.stat.descriptive.moment.StandardDeviation
- Constructs a StandardDeviation from an external second moment.
- StandardDeviation(StandardDeviation) -
Constructor for class org.apache.commons.math3.stat.descriptive.moment.StandardDeviation
- Copy constructor, creates a new
StandardDeviation identical
to the original
- StandardDeviation(boolean) -
Constructor for class org.apache.commons.math3.stat.descriptive.moment.StandardDeviation
- Contructs a StandardDeviation with the specified value for the
isBiasCorrected property.
- StandardDeviation(boolean, SecondMoment) -
Constructor for class org.apache.commons.math3.stat.descriptive.moment.StandardDeviation
- Contructs a StandardDeviation with the specified value for the
isBiasCorrected property and the supplied external moment.
- start(int, int, int, int, int, int) -
Method in class org.apache.commons.math3.linear.DefaultFieldMatrixChangingVisitor
- Start visiting a matrix.
- start(int, int, int, int, int, int) -
Method in class org.apache.commons.math3.linear.DefaultFieldMatrixPreservingVisitor
- Start visiting a matrix.
- start(int, int, int, int, int, int) -
Method in class org.apache.commons.math3.linear.DefaultRealMatrixChangingVisitor
- Start visiting a matrix.
- start(int, int, int, int, int, int) -
Method in class org.apache.commons.math3.linear.DefaultRealMatrixPreservingVisitor
- Start visiting a matrix.
- start(int, int, int, int, int, int) -
Method in interface org.apache.commons.math3.linear.FieldMatrixChangingVisitor
- Start visiting a matrix.
- start(int, int, int, int, int, int) -
Method in interface org.apache.commons.math3.linear.FieldMatrixPreservingVisitor
- Start visiting a matrix.
- start(int, int, int, int, int, int) -
Method in interface org.apache.commons.math3.linear.RealMatrixChangingVisitor
- Start visiting a matrix.
- start(int, int, int, int, int, int) -
Method in interface org.apache.commons.math3.linear.RealMatrixPreservingVisitor
- Start visiting a matrix.
- start(int, int, int) -
Method in interface org.apache.commons.math3.linear.RealVectorChangingVisitor
- Start visiting a vector.
- start(int, int, int) -
Method in interface org.apache.commons.math3.linear.RealVectorPreservingVisitor
- Start visiting a vector.
- start(double, double[], double) -
Method in class org.apache.commons.math3.ode.MultistepIntegrator
- Start the integration.
- start() -
Method in class org.apache.commons.math3.util.ResizableDoubleArray
- Deprecated. As of 3.1.
- stateVariation -
Variable in class org.apache.commons.math3.ode.sampling.NordsieckStepInterpolator
- State variation.
- StatisticalMultivariateSummary - Interface in org.apache.commons.math3.stat.descriptive
- Reporting interface for basic multivariate statistics.
- StatisticalSummary - Interface in org.apache.commons.math3.stat.descriptive
- Reporting interface for basic univariate statistics.
- StatisticalSummaryValues - Class in org.apache.commons.math3.stat.descriptive
- Value object representing the results of a univariate statistical summary.
- StatisticalSummaryValues(double, double, long, double, double, double) -
Constructor for class org.apache.commons.math3.stat.descriptive.StatisticalSummaryValues
- Constructor
- StatUtils - Class in org.apache.commons.math3.stat
- StatUtils provides static methods for computing statistics based on data
stored in double[] arrays.
- stepAccepted(double, double[]) -
Method in class org.apache.commons.math3.ode.events.EventState
- Acknowledge the fact the step has been accepted by the integrator.
- StepFunction - Class in org.apache.commons.math3.analysis.function
-
Step function.
- StepFunction(double[], double[]) -
Constructor for class org.apache.commons.math3.analysis.function.StepFunction
- Builds a step function from a list of arguments and the corresponding
values.
- StepHandler - Interface in org.apache.commons.math3.ode.sampling
- This interface represents a handler that should be called after
each successful step.
- stepHandlers -
Variable in class org.apache.commons.math3.ode.AbstractIntegrator
- Step handler.
- StepInterpolator - Interface in org.apache.commons.math3.ode.sampling
- This interface represents an interpolator over the last step
during an ODE integration.
- StepNormalizer - Class in org.apache.commons.math3.ode.sampling
- This class wraps an object implementing
FixedStepHandler
into a StepHandler. - StepNormalizer(double, FixedStepHandler) -
Constructor for class org.apache.commons.math3.ode.sampling.StepNormalizer
- Simple constructor.
- StepNormalizer(double, FixedStepHandler, StepNormalizerMode) -
Constructor for class org.apache.commons.math3.ode.sampling.StepNormalizer
- Simple constructor.
- StepNormalizer(double, FixedStepHandler, StepNormalizerBounds) -
Constructor for class org.apache.commons.math3.ode.sampling.StepNormalizer
- Simple constructor.
- StepNormalizer(double, FixedStepHandler, StepNormalizerMode, StepNormalizerBounds) -
Constructor for class org.apache.commons.math3.ode.sampling.StepNormalizer
- Simple constructor.
- StepNormalizerBounds - Enum in org.apache.commons.math3.ode.sampling
Step normalizer bounds settings.- StepNormalizerMode - Enum in org.apache.commons.math3.ode.sampling
Step normalizer modes.- stepSize -
Variable in class org.apache.commons.math3.ode.AbstractIntegrator
- Current stepsize.
- stepStart -
Variable in class org.apache.commons.math3.ode.AbstractIntegrator
- Current step start time.
- stirlingS2(int, int) -
Static method in class org.apache.commons.math3.util.ArithmeticUtils
- Returns the
Stirling number of the second kind, "
S(n,k)", the number of
ways of partitioning an n-element set into k non-empty
subsets.
- stop() -
Method in class org.apache.commons.math3.ode.events.EventState
- Check if the integration should be stopped at the end of the
current step.
- StoppingCondition - Interface in org.apache.commons.math3.genetics
- Algorithm used to determine when to stop evolution.
- store(PAIR) -
Method in class org.apache.commons.math3.optim.BaseMultiStartMultivariateOptimizer
- Method that will be called in order to store each found optimum.
- store(PointValuePair) -
Method in class org.apache.commons.math3.optim.nonlinear.scalar.MultiStartMultivariateOptimizer
- Method that will be called in order to store each found optimum.
- store(PointVectorValuePair) -
Method in class org.apache.commons.math3.optim.nonlinear.vector.MultiStartMultivariateVectorOptimizer
- Method that will be called in order to store each found optimum.
- StorelessCovariance - Class in org.apache.commons.math3.stat.correlation
- Covariance implementation that does not require input data to be
stored in memory.
- StorelessCovariance(int) -
Constructor for class org.apache.commons.math3.stat.correlation.StorelessCovariance
- Create a bias corrected covariance matrix with a given dimension.
- StorelessCovariance(int, boolean) -
Constructor for class org.apache.commons.math3.stat.correlation.StorelessCovariance
- Create a covariance matrix with a given number of rows and columns and the
indicated bias correction.
- StorelessUnivariateStatistic - Interface in org.apache.commons.math3.stat.descriptive
- Extends the definition of
UnivariateStatistic with
StorelessUnivariateStatistic.increment(double) and StorelessUnivariateStatistic.incrementAll(double[]) methods for adding
values and updating internal state. - storeTime(double) -
Method in class org.apache.commons.math3.ode.sampling.AbstractStepInterpolator
- Store the current step time.
- strictlyNegative() -
Method in class org.apache.commons.math3.dfp.Dfp
- Check if instance is strictly less than 0.
- strictlyPositive() -
Method in class org.apache.commons.math3.dfp.Dfp
- Check if instance is strictly greater than 0.
- subAndCheck(int, int) -
Static method in class org.apache.commons.math3.util.ArithmeticUtils
- Subtract two integers, checking for overflow.
- subAndCheck(long, long) -
Static method in class org.apache.commons.math3.util.ArithmeticUtils
- Subtract two long integers, checking for overflow.
- SubHyperplane<S extends Space> - Interface in org.apache.commons.math3.geometry.partitioning
- This interface represents the remaining parts of an hyperplane after
other parts have been chopped off.
- SubHyperplane.SplitSubHyperplane<U extends Space> - Class in org.apache.commons.math3.geometry.partitioning
- Class holding the results of the
split method. - SubHyperplane.SplitSubHyperplane(SubHyperplane<U>, SubHyperplane<U>) -
Constructor for class org.apache.commons.math3.geometry.partitioning.SubHyperplane.SplitSubHyperplane
- Build a SplitSubHyperplane from its parts.
- SubLine - Class in org.apache.commons.math3.geometry.euclidean.threed
- This class represents a subset of a
Line. - SubLine(Line, IntervalsSet) -
Constructor for class org.apache.commons.math3.geometry.euclidean.threed.SubLine
- Simple constructor.
- SubLine(Vector3D, Vector3D) -
Constructor for class org.apache.commons.math3.geometry.euclidean.threed.SubLine
- Create a sub-line from two endpoints.
- SubLine(Segment) -
Constructor for class org.apache.commons.math3.geometry.euclidean.threed.SubLine
- Create a sub-line from a segment.
- SubLine - Class in org.apache.commons.math3.geometry.euclidean.twod
- This class represents a sub-hyperplane for
Line. - SubLine(Hyperplane<Euclidean2D>, Region<Euclidean1D>) -
Constructor for class org.apache.commons.math3.geometry.euclidean.twod.SubLine
- Simple constructor.
- SubLine(Vector2D, Vector2D) -
Constructor for class org.apache.commons.math3.geometry.euclidean.twod.SubLine
- Create a sub-line from two endpoints.
- SubLine(Segment) -
Constructor for class org.apache.commons.math3.geometry.euclidean.twod.SubLine
- Create a sub-line from a segment.
- SubOrientedPoint - Class in org.apache.commons.math3.geometry.euclidean.oned
- This class represents sub-hyperplane for
OrientedPoint. - SubOrientedPoint(Hyperplane<Euclidean1D>, Region<Euclidean1D>) -
Constructor for class org.apache.commons.math3.geometry.euclidean.oned.SubOrientedPoint
- Simple constructor.
- SubPlane - Class in org.apache.commons.math3.geometry.euclidean.threed
- This class represents a sub-hyperplane for
Plane. - SubPlane(Hyperplane<Euclidean3D>, Region<Euclidean2D>) -
Constructor for class org.apache.commons.math3.geometry.euclidean.threed.SubPlane
- Simple constructor.
- substituteMostRecentElement(double) -
Method in class org.apache.commons.math3.util.ResizableDoubleArray
- Substitutes
value for the most recently added value.
- subtract(double) -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- '-' operator.
- subtract(DerivativeStructure) -
Method in class org.apache.commons.math3.analysis.differentiation.DerivativeStructure
- Compute this - a.
- subtract(double[], int, double[], int, double[], int) -
Method in class org.apache.commons.math3.analysis.differentiation.DSCompiler
- Perform subtraction of two derivative structures.
- Subtract - Class in org.apache.commons.math3.analysis.function
- Subtract the second operand from the first.
- Subtract() -
Constructor for class org.apache.commons.math3.analysis.function.Subtract
-
- subtract(PolynomialFunction) -
Method in class org.apache.commons.math3.analysis.polynomials.PolynomialFunction
- Subtract a polynomial from the instance.
- subtract(Complex) -
Method in class org.apache.commons.math3.complex.Complex
- Returns a
Complex whose value is
(this - subtrahend).
- subtract(double) -
Method in class org.apache.commons.math3.complex.Complex
- Returns a
Complex whose value is
(this - subtrahend).
- subtract(Quaternion, Quaternion) -
Static method in class org.apache.commons.math3.complex.Quaternion
- Subtracts two quaternions.
- subtract(Quaternion) -
Method in class org.apache.commons.math3.complex.Quaternion
- Subtracts a quaternion from the instance.
- subtract(Dfp) -
Method in class org.apache.commons.math3.dfp.Dfp
- Subtract x from this.
- subtract(double) -
Method in class org.apache.commons.math3.dfp.Dfp
- '-' operator.
- subtract(T) -
Method in interface org.apache.commons.math3.FieldElement
- Compute this - a.
- subtract(BigInteger) -
Method in class org.apache.commons.math3.fraction.BigFraction
-
Subtracts the value of an
BigInteger from the value of this
BigFraction, returning the result in reduced form.
- subtract(int) -
Method in class org.apache.commons.math3.fraction.BigFraction
-
Subtracts the value of an
integer from the value of this
BigFraction, returning the result in reduced form.
- subtract(long) -
Method in class org.apache.commons.math3.fraction.BigFraction
-
Subtracts the value of a
long from the value of this
BigFraction, returning the result in reduced form.
- subtract(BigFraction) -
Method in class org.apache.commons.math3.fraction.BigFraction
-
Subtracts the value of another fraction from the value of this one,
returning the result in reduced form.
- subtract(Fraction) -
Method in class org.apache.commons.math3.fraction.Fraction
- Subtracts the value of another fraction from the value of this one,
returning the result in reduced form.
- subtract(int) -
Method in class org.apache.commons.math3.fraction.Fraction
- Subtract an integer from the fraction.
- subtract(Vector<Euclidean1D>) -
Method in class org.apache.commons.math3.geometry.euclidean.oned.Vector1D
- Subtract a vector from the instance.
- subtract(double, Vector<Euclidean1D>) -
Method in class org.apache.commons.math3.geometry.euclidean.oned.Vector1D
- Subtract a scaled vector from the instance.
- subtract(FieldVector3D<T>) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.FieldVector3D
- Subtract a vector from the instance.
- subtract(Vector3D) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.FieldVector3D
- Subtract a vector from the instance.
- subtract(T, FieldVector3D<T>) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.FieldVector3D
- Subtract a scaled vector from the instance.
- subtract(T, Vector3D) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.FieldVector3D
- Subtract a scaled vector from the instance.
- subtract(double, FieldVector3D<T>) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.FieldVector3D
- Subtract a scaled vector from the instance.
- subtract(double, Vector3D) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.FieldVector3D
- Subtract a scaled vector from the instance.
- subtract(Vector<Euclidean3D>) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.Vector3D
- Subtract a vector from the instance.
- subtract(double, Vector<Euclidean3D>) -
Method in class org.apache.commons.math3.geometry.euclidean.threed.Vector3D
- Subtract a scaled vector from the instance.
- subtract(Vector<Euclidean2D>) -
Method in class org.apache.commons.math3.geometry.euclidean.twod.Vector2D
- Subtract a vector from the instance.
- subtract(double, Vector<Euclidean2D>) -
Method in class org.apache.commons.math3.geometry.euclidean.twod.Vector2D
- Subtract a scaled vector from the instance.
- subtract(Vector<S>) -
Method in interface org.apache.commons.math3.geometry.Vector
- Subtract a vector from the instance.
- subtract(double, Vector<S>) -
Method in interface org.apache.commons.math3.geometry.Vector
- Subtract a scaled vector from the instance.
- subtract(FieldMatrix<T>) -
Method in class org.apache.commons.math3.linear.AbstractFieldMatrix
- Subtract
m from this matrix.
- subtract(RealMatrix) -
Method in class org.apache.commons.math3.linear.AbstractRealMatrix
- Returns
this minus m.
- subtract(Array2DRowFieldMatrix<T>) -
Method in class org.apache.commons.math3.linear.Array2DRowFieldMatrix
- Subtract
m from this matrix.
- subtract(Array2DRowRealMatrix) -
Method in class org.apache.commons.math3.linear.Array2DRowRealMatrix
- Returns
this minus m.
- subtract(FieldVector<T>) -
Method in class org.apache.commons.math3.linear.ArrayFieldVector
- Compute
this minus v.
- subtract(ArrayFieldVector<T>) -
Method in class org.apache.commons.math3.linear.ArrayFieldVector
- Compute
this minus v.
- subtract(RealVector) -
Method in class org.apache.commons.math3.linear.ArrayRealVector
- Subtract
v from this vector.
- subtract(FieldMatrix<T>) -
Method in class org.apache.commons.math3.linear.BlockFieldMatrix
- Subtract
m from this matrix.
- subtract(BlockFieldMatrix<T>) -
Method in class org.apache.commons.math3.linear.BlockFieldMatrix
- Compute
this - m.
- subtract(RealMatrix) -
Method in class org.apache.commons.math3.linear.BlockRealMatrix
- Returns
this minus m.
- subtract(BlockRealMatrix) -
Method in class org.apache.commons.math3.linear.BlockRealMatrix
- Subtract
m from this matrix.
- subtract(DiagonalMatrix) -
Method in class org.apache.commons.math3.linear.DiagonalMatrix
- Returns
this minus m.
- subtract(FieldMatrix<T>) -
Method in interface org.apache.commons.math3.linear.FieldMatrix
- Subtract
m from this matrix.
- subtract(FieldVector<T>) -
Method in interface org.apache.commons.math3.linear.FieldVector
- Compute
this minus v.
- subtract(RealMatrix) -
Method in class org.apache.commons.math3.linear.OpenMapRealMatrix
- Deprecated. Returns
this minus m.
- subtract(OpenMapRealMatrix) -
Method in class org.apache.commons.math3.linear.OpenMapRealMatrix
- Deprecated. Subtract
m from this matrix.
- subtract(OpenMapRealVector) -
Method in class org.apache.commons.math3.linear.OpenMapRealVector
- Deprecated. Optimized method to subtract OpenMapRealVectors.
- subtract(RealVector) -
Method in class org.apache.commons.math3.linear.OpenMapRealVector
- Deprecated. Subtract
v from this vector.
- subtract(RealMatrix) -
Method in interface org.apache.commons.math3.linear.RealMatrix
- Returns
this minus m.
- subtract(RealVector) -
Method in class org.apache.commons.math3.linear.RealVector
- Subtract
v from this vector.
- subtract(SparseFieldVector<T>) -
Method in class org.apache.commons.math3.linear.SparseFieldVector
- Deprecated. Optimized method to compute
this minus v.
- subtract(FieldVector<T>) -
Method in class org.apache.commons.math3.linear.SparseFieldVector
- Deprecated. Compute
this minus v.
- subtract(double) -
Method in interface org.apache.commons.math3.RealFieldElement
- '-' operator.
- subtract(BigReal) -
Method in class org.apache.commons.math3.util.BigReal
- Compute this - a.
- subtract(Decimal64) -
Method in class org.apache.commons.math3.util.Decimal64
- Compute this - a.
- subtract(double) -
Method in class org.apache.commons.math3.util.Decimal64
- '-' operator.
- Sum - Class in org.apache.commons.math3.stat.descriptive.summary
- Returns the sum of the available values.
- Sum() -
Constructor for class org.apache.commons.math3.stat.descriptive.summary.Sum
- Create a Sum instance
- Sum(Sum) -
Constructor for class org.apache.commons.math3.stat.descriptive.summary.Sum
- Copy constructor, creates a new
Sum identical
to the original
- sum(double[]) -
Static method in class org.apache.commons.math3.stat.StatUtils
- Returns the sum of the values in the input array, or
Double.NaN if the array is empty.
- sum(double[], int, int) -
Static method in class org.apache.commons.math3.stat.StatUtils
- Returns the sum of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty.
- sumDifference(double[], double[]) -
Static method in class org.apache.commons.math3.stat.StatUtils
- Returns the sum of the (signed) differences between corresponding elements of the
input arrays -- i.e., sum(sample1[i] - sample2[i]).
- sumLog(double[]) -
Static method in class org.apache.commons.math3.stat.StatUtils
- Returns the sum of the natural logs of the entries in the input array, or
Double.NaN if the array is empty.
- sumLog(double[], int, int) -
Static method in class org.apache.commons.math3.stat.StatUtils
- Returns the sum of the natural logs of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty.
- SummaryStatistics - Class in org.apache.commons.math3.stat.descriptive
-
Computes summary statistics for a stream of data values added using the
addValue method. - SummaryStatistics() -
Constructor for class org.apache.commons.math3.stat.descriptive.SummaryStatistics
- Construct a SummaryStatistics instance
- SummaryStatistics(SummaryStatistics) -
Constructor for class org.apache.commons.math3.stat.descriptive.SummaryStatistics
- A copy constructor.
- SumOfLogs - Class in org.apache.commons.math3.stat.descriptive.summary
- Returns the sum of the natural logs for this collection of values.
- SumOfLogs() -
Constructor for class org.apache.commons.math3.stat.descriptive.summary.SumOfLogs
- Create a SumOfLogs instance
- SumOfLogs(SumOfLogs) -
Constructor for class org.apache.commons.math3.stat.descriptive.summary.SumOfLogs
- Copy constructor, creates a new
SumOfLogs identical
to the original
- SumOfSquares - Class in org.apache.commons.math3.stat.descriptive.summary
- Returns the sum of the squares of the available values.
- SumOfSquares() -
Constructor for class org.apache.commons.math3.stat.descriptive.summary.SumOfSquares
- Create a SumOfSquares instance
- SumOfSquares(SumOfSquares) -
Constructor for class org.apache.commons.math3.stat.descriptive.summary.SumOfSquares
- Copy constructor, creates a new
SumOfSquares identical
to the original
- sumSq(double[]) -
Static method in class org.apache.commons.math3.stat.StatUtils
- Returns the sum of the squares of the entries in the input array, or
Double.NaN if the array is empty.
- sumSq(double[], int, int) -
Static method in class org.apache.commons.math3.stat.StatUtils
- Returns the sum of the squares of the entries in the specified portion of
the input array, or
Double.NaN if the designated subarray
is empty.
- SymmLQ - Class in org.apache.commons.math3.linear
-
Implementation of the SYMMLQ iterative linear solver proposed by Paige and Saunders (1975).
- SymmLQ(int, double, boolean) -
Constructor for class org.apache.commons.math3.linear.SymmLQ
- Creates a new instance of this class, with default
stopping criterion.
- SymmLQ(IterationManager, double, boolean) -
Constructor for class org.apache.commons.math3.linear.SymmLQ
- Creates a new instance of this class, with default
stopping criterion and custom iteration manager.
- SynchronizedDescriptiveStatistics - Class in org.apache.commons.math3.stat.descriptive
- Implementation of
DescriptiveStatistics that
is safe to use in a multithreaded environment. - SynchronizedDescriptiveStatistics() -
Constructor for class org.apache.commons.math3.stat.descriptive.SynchronizedDescriptiveStatistics
- Construct an instance with infinite window
- SynchronizedDescriptiveStatistics(int) -
Constructor for class org.apache.commons.math3.stat.descriptive.SynchronizedDescriptiveStatistics
- Construct an instance with finite window
- SynchronizedDescriptiveStatistics(SynchronizedDescriptiveStatistics) -
Constructor for class org.apache.commons.math3.stat.descriptive.SynchronizedDescriptiveStatistics
- A copy constructor.
- SynchronizedMultivariateSummaryStatistics - Class in org.apache.commons.math3.stat.descriptive
- Implementation of
MultivariateSummaryStatistics that
is safe to use in a multithreaded environment. - SynchronizedMultivariateSummaryStatistics(int, boolean) -
Constructor for class org.apache.commons.math3.stat.descriptive.SynchronizedMultivariateSummaryStatistics
- Construct a SynchronizedMultivariateSummaryStatistics instance
- SynchronizedRandomGenerator - Class in org.apache.commons.math3.random
- Any
RandomGenerator implementation can be thread-safe if it
is used through an instance of this class. - SynchronizedRandomGenerator(RandomGenerator) -
Constructor for class org.apache.commons.math3.random.SynchronizedRandomGenerator
- Creates a synchronized wrapper for the given
RandomGenerator
instance.
- SynchronizedSummaryStatistics - Class in org.apache.commons.math3.stat.descriptive
- Implementation of
SummaryStatistics that
is safe to use in a multithreaded environment. - SynchronizedSummaryStatistics() -
Constructor for class org.apache.commons.math3.stat.descriptive.SynchronizedSummaryStatistics
- Construct a SynchronizedSummaryStatistics instance
- SynchronizedSummaryStatistics(SynchronizedSummaryStatistics) -
Constructor for class org.apache.commons.math3.stat.descriptive.SynchronizedSummaryStatistics
- A copy constructor.
sampleStats to mu.
StatisticalSummary instances, without the
assumption of equal subpopulation variances.
evaluate(double[], int, int) methods
to verify that the input parameters designate a subarray of positive length.
evaluate(double[], int, int) methods
to verify that the input parameters designate a subarray of positive length.
evaluate(double[], double[], int, int) methods
to verify that the begin and length parameters designate a subarray of positive length
and the weights are all non-negative, non-NaN, finite, and not all zero.
evaluate(double[], double[], int, int) methods
to verify that the begin and length parameters designate a subarray of positive length
and the weights are all non-negative, non-NaN, finite, and not all zero.
doubles.
doubles.
doubles.
DifferentiableMultivariateFunction interface itself is deprecated
DifferentiableMultivariateVectorFunction interface itself is deprecated
DifferentiableUnivariateFunction interface itself is deprecated
DifferentiableMultivariateFunction interface itself is deprecated
DifferentiableMultivariateFunction interface itself is deprecated
String representing this fraction, ie
"num / dem" or just "num" if the denominator is one.
String representing this fraction, ie
"num / dem" or just "num" if the denominator is one.
String is equal to
Double.toString(this.doubleValue())
DifferentiableUnivariateFunction interface itself is deprecated
Tricubic interpolation in three dimensions
F.- TricubicSplineInterpolatingFunction(double[], double[], double[], double[][][], double[][][], double[][][], double[][][], double[][][], double[][][], double[][][], double[][][]) - Constructor for class org.apache.commons.math3.analysis.interpolation.TricubicSplineInterpolatingFunction
- TricubicSplineInterpolator - Class in org.apache.commons.math3.analysis.interpolation
- Generates a tricubic interpolating function.
- TricubicSplineInterpolator() - Constructor for class org.apache.commons.math3.analysis.interpolation.TricubicSplineInterpolator
- trigamma(double) - Static method in class org.apache.commons.math3.special.Gamma
- Computes the trigamma function of x.
- trigger(int) - Method in interface org.apache.commons.math3.util.Incrementor.MaxCountExceededCallback
- Function called when the maximal count has been reached.
- TrivariateFunction - Interface in org.apache.commons.math3.analysis
- An interface representing a trivariate real function.
- TrivariateGridInterpolator - Interface in org.apache.commons.math3.analysis.interpolation
- Interface representing a trivariate real interpolating function where the sample points must be specified on a regular grid.
- trunc(DfpField.RoundingMode) - Method in class org.apache.commons.math3.dfp.Dfp
- Does the integer conversions with the specified rounding.
- tTest(double, double[], double) - Static method in class org.apache.commons.math3.stat.inference.TestUtils
- tTest(double, double[]) - Static method in class org.apache.commons.math3.stat.inference.TestUtils
- tTest(double, StatisticalSummary, double) - Static method in class org.apache.commons.math3.stat.inference.TestUtils
- tTest(double, StatisticalSummary) - Static method in class org.apache.commons.math3.stat.inference.TestUtils
- tTest(double[], double[], double) - Static method in class org.apache.commons.math3.stat.inference.TestUtils
- tTest(double[], double[]) - Static method in class org.apache.commons.math3.stat.inference.TestUtils
- tTest(StatisticalSummary, StatisticalSummary, double) - Static method in class org.apache.commons.math3.stat.inference.TestUtils
- tTest(StatisticalSummary, StatisticalSummary) - Static method in class org.apache.commons.math3.stat.inference.TestUtils
- TTest - Class in org.apache.commons.math3.stat.inference
- An implementation for Student's t-tests.
- TTest() - Constructor for class org.apache.commons.math3.stat.inference.TTest
- tTest(double, double[]) - Method in class org.apache.commons.math3.stat.inference.TTest
- Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the input array with the constant
mu.- tTest(double, double[], double) - Method in class org.apache.commons.math3.stat.inference.TTest
- Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which
sampleis drawn equalsmu.- tTest(double, StatisticalSummary) - Method in class org.apache.commons.math3.stat.inference.TTest
- Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the dataset described by
sampleStatswith the constantmu.- tTest(double, StatisticalSummary, double) - Method in class org.apache.commons.math3.stat.inference.TTest
- Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which the dataset described by
statsis drawn equalsmu.- tTest(double[], double[]) - Method in class org.apache.commons.math3.stat.inference.TTest
- Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays.
- tTest(double[], double[], double) - Method in class org.apache.commons.math3.stat.inference.TTest
- Performs a two-sided t-test evaluating the null hypothesis that
sample1andsample2are drawn from populations with the same mean, with significance levelalpha.- tTest(StatisticalSummary, StatisticalSummary) - Method in class org.apache.commons.math3.stat.inference.TTest
- Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances.
- tTest(StatisticalSummary, StatisticalSummary, double) - Method in class org.apache.commons.math3.stat.inference.TTest
- Performs a two-sided t-test evaluating the null hypothesis that
sampleStats1andsampleStats2describe datasets drawn from populations with the same mean, with significance levelalpha.- tTest(double, double, double, double) - Method in class org.apache.commons.math3.stat.inference.TTest
- Computes p-value for 2-sided, 1-sample t-test.
- tTest(double, double, double, double, double, double) - Method in class org.apache.commons.math3.stat.inference.TTest
- Computes p-value for 2-sided, 2-sample t-test.
- TWO - Static variable in class org.apache.commons.math3.fraction.BigFraction
- A fraction representing "2 / 1".
- TWO - Static variable in class org.apache.commons.math3.fraction.Fraction
- A fraction representing "2 / 1".
- TWO_FIFTHS - Static variable in class org.apache.commons.math3.fraction.BigFraction
- A fraction representing "2/5".
- TWO_FIFTHS - Static variable in class org.apache.commons.math3.fraction.Fraction
- A fraction representing "2/5".
- TWO_PI - Static variable in class org.apache.commons.math3.util.MathUtils
- 2 π.
- TWO_QUARTERS - Static variable in class org.apache.commons.math3.fraction.BigFraction
- A fraction representing "2/4".
- TWO_QUARTERS - Static variable in class org.apache.commons.math3.fraction.Fraction
- A fraction representing "2/4".
- TWO_THIRDS - Static variable in class org.apache.commons.math3.fraction.BigFraction
- A fraction representing "2/3".
- TWO_THIRDS - Static variable in class org.apache.commons.math3.fraction.Fraction
- A fraction representing "2/3".
ulp function.RandomVectorGenerator that generates vectors with uncorrelated
components.UniformCrossover policy using the given mixing ratio.
UniformRealDistribution.UniformRealDistribution(double, double) instead.
UniformRealDistribution.UniformRealDistribution(RandomGenerator, double, double)
instead.
MersenneTwister),
in order to generate the individual components.
Dfp function.UnivariateMatrixFunction representing a univariate differentiable matrix function.UnivariateVectorFunction representing a univariate differentiable vectorial function.UnivariateInterpolator
interface.UnivariateSolver objects.AbstractLeastSquaresOptimizer.computeWeightedJacobian(double[])
instead.
AbstractLeastSquaresOptimizer.computeResiduals(double[]),
BaseAbstractMultivariateVectorOptimizer.computeObjectiveValue(double[]), AbstractLeastSquaresOptimizer.computeCost(double[])
and AbstractLeastSquaresOptimizer.setCost(double) instead.
X, this method returns P(X >= x).
x.
x.
x.
x.
x.
ValueServer.ValueServer(RandomGenerator)
isBiasCorrected
property.
isBiasCorrected
property
isBiasCorrected
property and the supplied external second moment.
Variance identical
to the original
Double.NaN if the array is empty.
Double.NaN if the designated subarray
is empty.
lower < initial < upper.
lower < initial < upper.
curve fitting.AbstractLeastSquaresOptimizer.computeWeightedJacobian(double[]) instead.
0d as a Decimal64.
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