package stats
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Type Members
- case class ModeResult[T](mode: T, frequency: Int) extends Product with Serializable
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class
RandomizationTest[L] extends (Seq[L], Seq[L]) ⇒ Double
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
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object
DescriptiveStats
Provides utilities for descriptive statistics, like the mean and variance.
- object accumulateAndCount extends UFunc
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object
bincount extends UFunc
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)
- object corrcoeff extends UFunc
- object covmat extends UFunc
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object
digitize extends UFunc
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]
- object hist extends UFunc
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object
mean extends UFunc
A breeze.generic.UFunc for computing the mean of objects
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object
meanAndVariance extends UFunc
A breeze.generic.UFunc for computing the mean and sample variance of objects.
A breeze.generic.UFunc for computing the mean and sample variance of objects. This uses an efficient, numerically stable, one pass algorithm for computing both the mean and the variance.
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object
median extends UFunc
A breeze.generic.UFunc for computing the median of objects
- object mode extends UFunc
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object
stddev extends UFunc
Computes the *sample* standard deviation by calling variance and then sqrt'ing.
Computes the *sample* standard deviation by calling variance and then sqrt'ing. Note that this is different from Excel, numpy, etc.
Call stddev.population if you want that.
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object
variance extends UFunc
A breeze.generic.UFunc for computing the *sample* variance of objects.
A breeze.generic.UFunc for computing the *sample* variance of objects. The method just calls meanAndVariance and returns the second result.
Call variance.population if you want population variance