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Measures Methods

The Measures type exposes the following members.

Methods
  NameDescription
Public methodStatic memberContraHarmonicMean(Double)
Computes the contraharmonic mean of the given values.
Public methodStatic memberContraHarmonicMean(Double, Int32)
Computes the contraharmonic mean of the given values.
Public methodStatic memberCode exampleCorrelation(Double)
Calculates the correlation matrix for a matrix of samples.
Public methodStatic memberCode exampleCorrelation(Double)
Calculates the correlation matrix for a matrix of samples.
Public methodStatic memberCode exampleCorrelation(Double, Double, Double)
Calculates the correlation matrix for a matrix of samples.
Public methodStatic memberCode exampleCorrelation(Double, Double, Double)
Calculates the correlation matrix for a matrix of samples.
Public methodStatic memberCovariance(Double)
Calculates the covariance matrix of a sample matrix.
Public methodStatic memberCovariance(Double)
Calculates the covariance matrix of a sample matrix.
Public methodStatic memberCovariance(Double, Double)
Calculates the covariance matrix of a sample matrix.
Public methodStatic memberCovariance(Double, Int32)
Calculates the covariance matrix of a sample matrix.
Public methodStatic memberCovariance(Double, Double)
Calculates the covariance matrix of a sample matrix.
Public methodStatic memberCovariance(Double, Int32)
Calculates the covariance matrix of a sample matrix.
Public methodStatic memberCovariance(Double, Double, Boolean)
Computes the Covariance between two arrays of values.
Public methodStatic memberCovariance(Double, Double, Double, Double, Boolean)
Computes the Covariance between two arrays of values.
Public methodStatic memberEntropy(Double)
Computes the entropy for the given values.
Public methodStatic memberEntropy(Double)
Computes the entropy for the given values.
Public methodStatic memberEntropy(Boolean, Boolean)
Computes the entropy function between an expected value and a predicted value.
Public methodStatic memberEntropy(Boolean, Double)
Computes the entropy function between an expected value and a predicted value between 0 and 1.
Public methodStatic memberEntropy(IListInt32, Int32)
Computes the entropy for the given values.
Public methodStatic memberEntropy(Double, Double)
Computes the entropy for the given values.
Public methodStatic memberEntropy(Double, Double)
Computes the entropy for the given values.
Public methodStatic memberEntropy(Double, FuncDouble, Double)
Computes the entropy function for a set of numerical values in a given Probability Density Function (pdf).
Public methodStatic memberEntropy(Int32, IntRange)
Computes the entropy for the given values.
Public methodStatic memberEntropy(Int32, Int32)
Computes the entropy for the given values.
Public methodStatic memberEntropy(IListInt32, Int32, Int32)
Computes the entropy for the given values.
Public methodStatic memberEntropy(Double, Double, FuncDouble, Double)
Computes the entropy function for a set of numerical values in a given Probability Density Function (pdf).
Public methodStatic memberEntropy(Int32, Int32, Int32)
Computes the entropy for the given values.
Public methodStatic memberCode exampleExponentialWeightedCovariance(Double, Double, Boolean)
Calculates the exponentially weighted covariance matrix.
Public methodStatic memberCode exampleExponentialWeightedCovariance(Double, Int32, Double, Boolean)
Calculates the exponentially weighted covariance matrix.
Public methodStatic memberCode exampleExponentialWeightedMean(Double, Double)
Calculates the exponentially weighted mean.
Public methodStatic memberCode exampleExponentialWeightedMean(Double, Double)
Calculates the exponentially weighted mean vector.
Public methodStatic memberCode exampleExponentialWeightedMean(Double, Int32, Double)
Calculates the exponentially weighted mean.
Public methodStatic memberCode exampleExponentialWeightedMean(Double, Int32, Double)
Calculates the exponentially weighted mean vector.
Public methodStatic memberCode exampleExponentialWeightedVariance(Double, Double, Boolean)
Calculates the exponentially weighted variance.
Public methodStatic memberCode exampleExponentialWeightedVariance(Double, Int32, Double, Boolean)
Calculates the exponentially weighted variance.
Public methodStatic memberGeometricMean(Double)
Computes the Geometric mean of the given values.
Public methodStatic memberGeometricMean(Int32)
Computes the geometric mean of the given values.
Public methodStatic memberGetHistogramRange
Get range around median of an histogram containing specified percentage of values.
Public methodStatic memberGrandMean
Computes the (weighted) grand mean of a set of samples.
Public methodStatic memberHistogramEntropy
Calculate entropy value of an histogram.
Public methodStatic memberHistogramMax
Gets the maximum value in the histogram.
Public methodStatic memberHistogramMean
Calculate mean value of an histogram.
Public methodStatic memberHistogramMedian
Calculate median value of an histogram.
Public methodStatic memberHistogramMin
Gets the minimum value in the histogram.
Public methodStatic memberHistogramMode
Calculate mode value of an histogram.
Public methodStatic memberHistogramStandardDeviation(Int32)
Calculate standard deviation of an histogram.
Public methodStatic memberHistogramStandardDeviation(Int32, Double)
Calculate standard deviation of an histogram.
Public methodStatic memberHistogramSum
Calculates the total number of samples in a histogram.
Public methodStatic memberKurtosis(Double, Boolean)
Computes the Kurtosis vector for the given matrix.
Public methodStatic memberKurtosis(Double, Boolean)
Computes the Kurtosis for the given values.
Public methodStatic memberKurtosis(Double, Boolean)
Computes the Kurtosis vector for the given matrix.
Public methodStatic memberKurtosis(Double, Double, Boolean)
Computes the sample Kurtosis vector for the given matrix.
Public methodStatic memberKurtosis(Double, Double, Boolean)
Computes the Kurtosis for the given values.
Public methodStatic memberKurtosis(Double, Double, Boolean)
Computes the Kurtosis vector for the given matrix.
Public methodStatic memberLogGeometricMean(Double)
Computes the log geometric mean of the given values.
Public methodStatic memberLogGeometricMean(Int32)
Computes the log geometric mean of the given values.
Public methodStatic memberLowerQuartile
Computes the lower quartile (Q1) for the given data.
Public methodStatic memberMean(Double)
Computes the mean value across all dimensions of the given matrix.
Public methodStatic memberMean(Double)
Computes the mean of the given values.
Public methodStatic memberMean(Double)
Computes the mean value across all dimensions of the given matrix.
Public methodStatic memberMean(Int32)
Computes the mean of the given values.
Public methodStatic memberMean(Single)
Computes the mean of the given values.
Public methodStatic memberMean(UInt16)
Computes the mean of the given values.
Public methodStatic memberMean(Double, Double)
Calculates the matrix Mean vector.
Public methodStatic memberCode exampleMean(Double, Int32)
Calculates the matrix Mean vector.
Public methodStatic memberMean(Double, Double)
Calculates the matrix Mean vector.
Public methodStatic memberCode exampleMean(Double, Int32)
Calculates the matrix Mean vector.
Public methodStatic memberMedian(Double, QuantileMethod)
Calculates the matrix Medians vector.
Public methodStatic memberMedian(Double, QuantileMethod)
Calculates the matrix Medians vector.
Public methodStatic memberMedian(Double, Boolean, QuantileMethod, Boolean)
Computes the Median of the given values.
Public methodStatic memberMedian(Int32, Boolean, QuantileMethod, Boolean)
Computes the Median of the given values.
Public methodStatic memberModeT(T)
Calculates the matrix Modes vector.
Public methodStatic memberModeT(T)
Computes the Mode of the given values.
Public methodStatic memberModeT(T)
Calculates the matrix Modes vector.
Public methodStatic memberModeT(T, Int32)
Computes the Mode of the given values.
Public methodStatic memberModeT(T, Boolean, Boolean)
Computes the Mode of the given values.
Public methodStatic memberModeT(T, Int32, Boolean, Boolean)
Computes the Mode of the given values.
Public methodStatic memberPooledCovariance
Calculates the weighted pooled covariance matrix from a set of covariance matrices.
Public methodStatic memberPooledStandardDeviation(Double)
Computes the pooled standard deviation of the given values.
Public methodStatic memberPooledStandardDeviation(Boolean, Double)
Computes the pooled standard deviation of the given values.
Public methodStatic memberPooledStandardDeviation(Int32, Double, Boolean)
Computes the pooled standard deviation of the given values.
Public methodStatic memberPooledVariance(Double)
Computes the pooled variance of the given values.
Public methodStatic memberPooledVariance(Boolean, Double)
Computes the pooled variance of the given values.
Public methodStatic memberPooledVariance(Int32, Double, Boolean)
Computes the pooled variance of the given values.
Public methodStatic memberQuantile
Computes single quantile for the given sequence.
Public methodStatic memberQuantiles
Computes multiple quantiles for the given sequence.
Public methodStatic memberQuartiles(Double, DoubleRange, QuantileMethod)
Computes the Quartiles of the given values.
Public methodStatic memberQuartiles(Double, DoubleRange, QuantileMethod)
Computes the Quartiles of the given values.
Public methodStatic memberQuartiles(Double, Double, Double, QuantileMethod)
Computes the Quartiles of the given values.
Public methodStatic memberQuartiles(Double, Double, Double, QuantileMethod)
Computes the Quartiles of the given values.
Public methodStatic memberQuartiles(Double, DoubleRange, Boolean, QuantileMethod, Boolean)
Computes the Quartiles of the given values.
Public methodStatic memberQuartiles(Double, Double, Double, Boolean, QuantileMethod, Boolean)
Computes the Quartiles of the given values.
Public methodStatic memberScatter(Double, Double)
Calculates the scatter matrix of a sample matrix.
Public methodStatic memberScatter(Double, Double)
Calculates the scatter matrix of a sample matrix.
Public methodStatic memberScatter(Double, Double, Double)
Calculates the scatter matrix of a sample matrix.
Public methodStatic memberScatter(Double, Double, Int32)
Calculates the scatter matrix of a sample matrix.
Public methodStatic memberScatter(Double, Double, Int32)
Calculates the scatter matrix of a sample matrix.
Public methodStatic memberScatter(Double, Double, Double)
Calculates the scatter matrix of a sample matrix.
Public methodStatic memberScatter(Double, Double, Int32)
Calculates the scatter matrix of a sample matrix.
Public methodStatic memberScatter(Double, Double, Double, Int32)
Calculates the scatter matrix of a sample matrix.
Public methodStatic memberScatter(Double, Double, Double, Int32)
Calculates the scatter matrix of a sample matrix.
Public methodStatic memberSkewness(Double, Boolean)
Computes the Skewness for the given values.
Public methodStatic memberSkewness(Double, Boolean)
Computes the Skewness for the given values.
Public methodStatic memberSkewness(Double, Boolean)
Computes the Skewness for the given values.
Public methodStatic memberSkewness(Double, Double, Boolean)
Computes the Skewness vector for the given matrix.
Public methodStatic memberSkewness(Double, Double, Boolean)
Computes the Skewness for the given values.
Public methodStatic memberSkewness(Double, Double, Boolean)
Computes the Skewness vector for the given matrix.
Public methodStatic memberStandardDeviation(Double)
Calculates the matrix Standard Deviations vector.
Public methodStatic memberStandardDeviation(Single)
Computes the Standard Deviation of the given values.
Public methodStatic memberStandardDeviation(Double, Double)
Calculates the matrix Standard Deviations vector.
Public methodStatic memberStandardDeviation(Double, Boolean)
Computes the Standard Deviation of the given values.
Public methodStatic memberStandardDeviation(Double, Boolean)
Calculates the matrix Standard Deviations vector.
Public methodStatic memberStandardDeviation(Int32, Double)
Computes the Standard Deviation of the given values.
Public methodStatic memberStandardDeviation(Single, Single)
Computes the Standard Deviation of the given values.
Public methodStatic memberStandardDeviation(Double, Double, Boolean)
Computes the Standard Deviation of the given values.
Public methodStatic memberStandardDeviation(Double, Double, Boolean)
Calculates the matrix Standard Deviations vector.
Public methodStatic memberStandardError(Double)
Computes the Standard Error vector for a given matrix.
Public methodStatic memberStandardError(Double)
Computes the Standard Error for a sample size, which estimates the standard deviation of the sample mean based on the population mean.
Public methodStatic memberStandardError(Int32, Double)
Computes the Standard Error for a sample size, which estimates the standard deviation of the sample mean based on the population mean.
Public methodStatic memberStandardError(Int32, Double)
Computes the Standard Error vector for a given matrix.
Public methodStatic memberTruncatedMean
Computes the truncated (trimmed) mean of the given values.
Public methodStatic memberUpperQuartile
Computes the upper quartile (Q3) for the given data.
Public methodStatic memberVariance(Double)
Calculates the matrix Variance vector.
Public methodStatic memberVariance(Double)
Computes the Variance of the given values.
Public methodStatic memberVariance(Double)
Calculates the matrix Variance vector.
Public methodStatic memberVariance(Int32)
Computes the Variance of the given values.
Public methodStatic memberVariance(Single)
Computes the Variance of the given values.
Public methodStatic memberVariance(Double, Double)
Calculates the matrix Variance vector.
Public methodStatic memberVariance(Double, Boolean)
Computes the Variance of the given values.
Public methodStatic memberVariance(Double, Double)
Computes the Variance of the given values.
Public methodStatic memberVariance(Int32, Boolean)
Computes the Variance of the given values.
Public methodStatic memberVariance(Single, Single)
Computes the Variance of the given values.
Public methodStatic memberVariance(Double, Double, Boolean)
Computes the Variance of the given values.
Public methodStatic memberVariance(Double, Double, Boolean)
Calculates the matrix Variance vector.
Public methodStatic memberVariance(Int32, Double, Boolean)
Computes the Variance of the given values.
Public methodStatic memberWeightedCovariance(Double, Double, Double)
Calculates the covariance matrix of a sample matrix.
Public methodStatic memberWeightedCovariance(Double, Double, Int32)
Calculates the covariance matrix of a sample matrix.
Public methodStatic memberWeightedCovariance(Double, Int32, Int32)
Calculates the covariance matrix of a sample matrix.
Public methodStatic memberWeightedCovariance(Double, Double, Double, Int32)
Calculates the covariance matrix of a sample matrix.
Public methodStatic memberWeightedCovariance(Double, Int32, Double, Int32)
Calculates the covariance matrix of a sample matrix.
Public methodStatic memberWeightedEntropy(IListInt32, IListDouble, Int32)
Computes the entropy for the given values.
Public methodStatic memberWeightedEntropy(Double, Double, FuncDouble, Double)
Computes the entropy function for a set of numerical values in a given Probability Density Function (pdf).
Public methodStatic memberWeightedEntropy(Double, Double, Int32)
Computes the entropy for the given values.
Public methodStatic memberWeightedEntropy(Double, Int32, FuncDouble, Double)
Computes the entropy function for a set of numerical values in a given Probability Density Function (pdf).
Public methodStatic memberWeightedEntropy(Int32, Double, Int32)
Computes the entropy for the given values.
Public methodStatic memberWeightedEntropy(IListInt32, IListDouble, Int32, Int32)
Computes the entropy for the given values.
Public methodStatic memberWeightedEntropy(Double, Double, Int32, Int32)
Computes the entropy for the given values.
Public methodStatic memberWeightedEntropy(Int32, Double, Int32, Int32)
Computes the entropy for the given values.
Public methodStatic memberWeightedMax(Double, Double, Int32, Boolean)
Gets the maximum value in a vector of observations that has a weight higher than zero.
Public methodStatic memberWeightedMax(Double, Int32, Int32, Boolean)
Gets the maximum value in a vector of observations that has a weight higher than zero.
Public methodStatic memberWeightedMean(Double, Double)
Calculates the weighted matrix Mean vector.
Public methodStatic memberWeightedMean(Double, Int32)
Calculates the weighted matrix Mean vector.
Public methodStatic memberWeightedMean(Double, Double)
Computes the Weighted Mean of the given values.
Public methodStatic memberWeightedMean(Double, Int32)
Computes the Weighted Mean of the given values.
Public methodStatic memberWeightedMean(Double, Double)
Calculates the weighted matrix Mean vector.
Public methodStatic memberWeightedMean(Double, Int32)
Calculates the weighted matrix Mean vector.
Public methodStatic memberWeightedMean(Double, Double, Int32)
Calculates the weighted matrix Mean vector.
Public methodStatic memberWeightedMean(Double, Int32, Int32)
Calculates the weighted matrix Mean vector.
Public methodStatic memberWeightedMean(Double, Double, Int32)
Calculates the weighted matrix Mean vector.
Public methodStatic memberWeightedMean(Double, Int32, Int32)
Calculates the weighted matrix Mean vector.
Public methodStatic memberWeightedMin(Double, Double, Int32, Boolean)
Gets the minimum value in a vector of observations that has a weight higher than zero.
Public methodStatic memberWeightedMin(Double, Int32, Int32, Boolean)
Gets the minimum value in a vector of observations that has a weight higher than zero.
Public methodStatic memberWeightedModeT(T, Double, Boolean, Boolean)
Computes the Mode of the given values.
Public methodStatic memberWeightedModeT(T, Int32, Boolean, Boolean)
Computes the Mode of the given values.
Public methodStatic memberWeightedScatter(Double, Double, Double, Double, Int32)
Calculates the scatter matrix of a sample matrix.
Public methodStatic memberWeightedScatter(Double, Int32, Double, Double, Int32)
Calculates the scatter matrix of a sample matrix.
Public methodStatic memberWeightedStandardDeviation(Double, Double)
Calculates the matrix Standard Deviations vector.
Public methodStatic memberWeightedStandardDeviation(Double, Int32)
Calculates the matrix Standard Deviations vector.
Public methodStatic memberWeightedStandardDeviation(Double, Double)
Computes the Standard Deviation of the given values.
Public methodStatic memberWeightedStandardDeviation(Double, Int32)
Computes the Standard Deviation of the given values.
Public methodStatic memberWeightedStandardDeviation(Double, Double, Double)
Calculates the matrix Standard Deviations vector.
Public methodStatic memberWeightedStandardDeviation(Double, Int32, Double)
Calculates the matrix Standard Deviations vector.
Public methodStatic memberWeightedStandardDeviation(Double, Double, WeightType)
Computes the Standard Deviation of the given values.
Public methodStatic memberWeightedStandardDeviation(Double, Double, Double)
Computes the Standard Deviation of the given values.
Public methodStatic memberWeightedStandardDeviation(Double, Int32, Double)
Computes the Standard Deviation of the given values.
Public methodStatic memberWeightedStandardDeviation(Double, Double, Boolean)
Calculates the matrix Standard Deviations vector.
Public methodStatic memberWeightedStandardDeviation(Double, Int32, Boolean)
Calculates the matrix Standard Deviations vector.
Public methodStatic memberWeightedStandardDeviation(Double, Double, Boolean, WeightType)
Computes the Standard Deviation of the given values.
Public methodStatic memberWeightedStandardDeviation(Double, Int32, Double, Boolean)
Computes the Standard Deviation of the given values.
Public methodStatic memberWeightedStandardDeviation(Double, Double, Double, Boolean)
Calculates the matrix Standard Deviations vector.
Public methodStatic memberWeightedStandardDeviation(Double, Int32, Double, Boolean)
Calculates the matrix Standard Deviations vector.
Public methodStatic memberWeightedStandardDeviation(Double, Double, Double, Boolean, WeightType)
Computes the Standard Deviation of the given values.
Public methodStatic memberWeightedVariance(Double, Double)
Calculates the matrix Variance vector.
Public methodStatic memberWeightedVariance(Double, Int32)
Calculates the matrix Variance vector.
Public methodStatic memberWeightedVariance(Double, Double)
Computes the weighted Variance of the given values.
Public methodStatic memberWeightedVariance(Double, Int32)
Computes the weighted Variance of the given values.
Public methodStatic memberWeightedVariance(Double, Double)
Calculates the matrix Variance vector.
Public methodStatic memberWeightedVariance(Double, Int32)
Calculates the matrix Variance vector.
Public methodStatic memberWeightedVariance(Double, Double, WeightType)
Calculates the matrix Variance vector.
Public methodStatic memberWeightedVariance(Double, Double, Double)
Calculates the matrix Variance vector.
Public methodStatic memberWeightedVariance(Double, Int32, Double)
Calculates the matrix Variance vector.
Public methodStatic memberWeightedVariance(Double, Double, WeightType)
Computes the weighted Variance of the given values.
Public methodStatic memberWeightedVariance(Double, Double, Boolean)
Computes the weighted Variance of the given values.
Public methodStatic memberWeightedVariance(Double, Double, Double)
Computes the weighted Variance of the given values.
Public methodStatic memberWeightedVariance(Double, Int32, Boolean)
Computes the weighted Variance of the given values.
Public methodStatic memberWeightedVariance(Double, Int32, Double)
Computes the weighted Variance of the given values.
Public methodStatic memberWeightedVariance(Double, Double, Double)
Calculates the matrix Variance vector.
Public methodStatic memberWeightedVariance(Double, Int32, Double)
Calculates the matrix Variance vector.
Public methodStatic memberWeightedVariance(Double, Double, Double, WeightType)
Calculates the matrix Variance vector.
Public methodStatic memberWeightedVariance(Double, Int32, Double, Boolean)
Calculates the matrix Variance vector.
Public methodStatic memberWeightedVariance(Double, Double, Boolean, WeightType)
Computes the weighted Variance of the given values.
Public methodStatic memberWeightedVariance(Double, Int32, Double, Boolean)
Computes the weighted Variance of the given values.
Public methodStatic memberWeightedVariance(Double, Int32, Double, Boolean)
Calculates the matrix Variance vector.
Public methodStatic memberWeightedVariance(Double, Double, Double, Boolean, WeightType)
Calculates the matrix Variance vector.
Public methodStatic memberWeightedVariance(Double, Double, Double, Boolean, WeightType)
Computes the weighted Variance of the given values.
Public methodStatic memberWeightedVariance(Double, Double, Double, Boolean, WeightType)
Calculates the matrix Variance vector.
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