Package

breeze

stats

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package stats

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Type Members

  1. trait DescriptiveStats extends AnyRef

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  2. case class MeanAndVariance(mean: Double, variance: Double, count: Long) extends Product with Serializable

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  3. case class ModeResult[T](mode: T, frequency: Int) extends Product with Serializable

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  4. class RandomizationTest[L] extends (Seq[L], Seq[L]) ⇒ Double

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    Implements statistical significance testing for the output of two systems by randomization.

    Implements statistical significance testing for the output of two systems by randomization. This system assumes they're on the same dataset, which changes the procedure. Follows Teh, 2000 More accurate tests for the statistical significance of result differences.

    Labels must have .equals.

Value Members

  1. object DescriptiveStats

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    Provides utilities for descriptive statistics, like the mean and variance.

  2. object accumulateAndCount extends UFunc

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  3. object bincount extends UFunc

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    A breeze.generic.UFunc for counting bins.

    A breeze.generic.UFunc for counting bins.

    If passed a traversable object full of Int's, provided those ints are larger than 0, it will return an array of the bin counts. E.g.: bincount(DenseVector[Int](0,1,2,3,1,3,3,3)) == DenseVector[Int](1,2,1,4)

    One can also call this on two dense vectors - the second will be treated as an array of weights. E.g.: val x = DenseVector[Int](0,1,2,3,1) val weights = DenseVector[Double](1.0,2.0,1.0,7.0,1.0) result is bincount(x, weights) == DenseVector[Double](1.0,3.0,1,7.0)

    Definition Classes
    DescriptiveStats
  4. object corrcoeff extends UFunc

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    Definition Classes
    DescriptiveStats
  5. object covmat extends UFunc

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    Definition Classes
    DescriptiveStats
  6. object digitize extends UFunc

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    A breeze.generic.UFunc for digitizing arrays.

    A breeze.generic.UFunc for digitizing arrays.

    Each element in the bins array is assumed to be the *right* endpoint of a given bin. For instance, bins=[1,3,5] represents a bin from (-infty,1], (1,3], (3,5] and (5,\infty). The result returned is the index of the bin of the inputs.

    E.g., digitize([-3, 0.5, 1, 1.5, 4], [0,1,2]) = [0, 1, 1, 2, 3]

    Definition Classes
    DescriptiveStats
  7. package distributions

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  8. object hist extends UFunc

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  9. package hypothesis

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    This package contains hypothesis tests.

  10. package mcmc

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  11. object mean extends UFunc

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    A breeze.generic.UFunc for computing the mean of objects

    A breeze.generic.UFunc for computing the mean of objects

    Definition Classes
    DescriptiveStats
  12. object meanAndVariance extends UFunc

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    A breeze.generic.UFunc for computing the mean and variance of objects.

    A breeze.generic.UFunc for computing the mean and variance of objects. This uses an efficient, numerically stable, one pass algorithm for computing both the mean and the variance.

    Definition Classes
    DescriptiveStats
  13. object median extends UFunc

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    A breeze.generic.UFunc for computing the median of objects

    A breeze.generic.UFunc for computing the median of objects

    Definition Classes
    DescriptiveStats
  14. object mode extends UFunc

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    Definition Classes
    DescriptiveStats
  15. package random

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  16. package regression

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  17. object stddev extends UFunc

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    Computes the standard deviation by calling variance and then sqrt'ing

    Computes the standard deviation by calling variance and then sqrt'ing

    Definition Classes
    DescriptiveStats
  18. object variance extends UFunc

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    A breeze.generic.UFunc for computing the variance of objects.

    A breeze.generic.UFunc for computing the variance of objects. The method just calls meanAndVariance and returns the second result.

    Definition Classes
    DescriptiveStats

Inherited from DescriptiveStats

Inherited from AnyRef

Inherited from Any

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