Package org.cloudbus.cloudsim.util

Class Regression

java.lang.Object

org.cloudbus.cloudsim.util.Regression

public final class Regression
extends Object

Provides utility methods to compute regressions.

Since:

CloudSim Plus 7.0.1

See Also:

• Regression Analysis

Method Summary

Modifier and Type	Method	Description
static List<Double>	correlationCoefficients(double[][] data)	Computes correlation coefficients for a set of data.
static double[]	getLoessParameterEstimates(double... y)	Gets the Local Regression (LOESS) parameter estimates.
static double[]	getRobustLoessParameterEstimates(double... y)	Gets the robust LOESS parameter estimates.
static org.apache.commons.math3.stat.regression.OLSMultipleLinearRegression	newLinearRegression(double[][] x, double[] y)	Creates a a multiple linear regression.
static org.apache.commons.math3.stat.regression.SimpleRegression	newLinearRegression(double[] x, double[] y)	Creates a simple linear regression.
static org.apache.commons.math3.stat.regression.SimpleRegression	newWeightedLinearRegression(double[] x, double[] y, double[] weights)	Creates a weighted linear regression.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Method Details

newLinearRegression

public static org.apache.commons.math3.stat.regression.SimpleRegression newLinearRegression(double[] x,
 double[] y)

Creates a simple linear regression.

Parameters:

x - the independent variable

y - the dependent variable

Returns:

newLinearRegression

public static org.apache.commons.math3.stat.regression.OLSMultipleLinearRegression newLinearRegression(double[][] x,
 double[] y)

Creates a a multiple linear regression.

Parameters:

x - the independent variable

y - the dependent variable

Returns:

newWeightedLinearRegression

public static org.apache.commons.math3.stat.regression.SimpleRegression newWeightedLinearRegression(double[] x,
 double[] y,
 double[] weights)

Creates a weighted linear regression.

Parameters:

x - the independent variable

y - the dependent variable

weights - the weights to apply to x and y

Returns:

getLoessParameterEstimates

public static double[] getLoessParameterEstimates(double... y)

Gets the Local Regression (LOESS) parameter estimates.

Parameters:

y - the dependent variable

Returns:

the Loess parameter estimates

See Also:

• LOESS

getRobustLoessParameterEstimates

public static double[] getRobustLoessParameterEstimates(double... y)

Gets the robust LOESS parameter estimates.

Parameters:

y - the dependent variable

Returns:

the robust loess parameter estimates

correlationCoefficients

public static List<Double> correlationCoefficients(double[][] data)

Computes correlation coefficients for a set of data.

Parameters:

data - the data to compute the correlation coefficients

Returns:

the correlation coefficients