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Tools Methods

The Tools type exposes the following members.

Methods
  NameDescription
Public methodStatic memberCenter(Double, Boolean)
Centers column data, subtracting the empirical mean from each variable.
Public methodStatic memberCenter(Double, Double)
Centers an observation, subtracting the empirical mean from each element in the observation vector.
Public methodStatic memberCenter(Double, Boolean)
Centers column data, subtracting the empirical mean from each variable.
Public methodStatic memberCenter(Double, Double, Boolean)
Centers column data, subtracting the empirical mean from each variable.
Public methodStatic memberCenter(Double, Double, Double)
Centers an observation, subtracting the empirical mean from each element in the observation vector.
Public methodStatic memberCenter(Double, Double, Boolean)
Centers column data, subtracting the empirical mean from each variable.
Public methodStatic memberDetermination
Gets the coefficient of determination, as known as the R-Squared (R²)
Public methodStatic memberDistance
Computes the kernel distance for a kernel function even if it doesn't implement the IDistance interface. Can be used to check the proper implementation of the distance function.
Public methodStatic memberExpand(Int32) Obsolete.
Public methodStatic memberExpand(Int32, Int32) Obsolete.
Public methodStatic memberExpand(Int32, Double, Double) Obsolete.
Public methodStatic memberExpand(Int32, Int32, Int32) Obsolete.
Public methodStatic memberExpand(Int32, Int32, Double, Double) Obsolete.
Public methodStatic memberExpand(Int32, Int32, Int32, Int32) Obsolete.
Public methodStatic memberFitTDistribution(Double, Double)
Creates a new distribution that has been fit to a given set of observations.
Public methodStatic memberFitTDistribution(Double, Double)
Creates a new distribution that has been fit to a given set of observations.
Public methodStatic memberFitTDistribution, TOptions(Double, TOptions, Double)
Creates a new distribution that has been fit to a given set of observations.
Public methodStatic memberFitTDistribution, TOptions(Double, TOptions, Double)
Creates a new distribution that has been fit to a given set of observations.
Public methodStatic memberFitNewTDistribution, TObservations(TDistribution, TObservations, Double)
Creates a new distribution that has been fit to a given set of observations.
Public methodStatic memberFitNewTDistribution, TObservations, TOptions(TDistribution, TObservations, TOptions, Double)
Creates a new distribution that has been fit to a given set of observations.
Public methodStatic memberGroup Obsolete.
Public methodStatic memberInnerFence
Creates Tukey's box plot inner fence.
Public methodStatic memberOuterFence
Creates Tukey's box plot outer fence.
Public methodStatic memberProportions(Int32, Int32) Obsolete.
Public methodStatic memberProportions(Int32, Int32, Int32) Obsolete.
Public methodStatic memberRandom Obsolete.
Obsolete. Please use Sample(Int32) instead.
Public methodStatic memberRandomCovariance
Public methodStatic memberRandomGroups(Int32, Double) Obsolete.
Obsolete. Please use Random(Int32, Double) instead.
Public methodStatic memberRandomGroups(Int32, Int32) Obsolete.
Obsolete. Please use Random(Int32, Int32) instead.
Public methodStatic memberRandomGroups(Int32, Int32, Int32) Obsolete.
Public methodStatic memberRandomSample Obsolete.
Obsolete. Please use Sample(Int32, Int32) instead.
Public methodStatic memberRank(Double, Boolean, Boolean)
Gets the rank of a sample, often used with order statistics.
Public methodStatic memberRank(Double, Boolean, Boolean, Boolean)
Gets the rank of a sample, often used with order statistics.
Public methodStatic memberShuffleT(IListT) Obsolete.
Public methodStatic memberShuffleT(T) Obsolete.
Public methodStatic memberStandardize(Double, Boolean)
Standardizes column data, removing the empirical standard deviation from each variable.
Public methodStatic memberStandardize(Double, Boolean)
Standardizes column data, removing the empirical standard deviation from each variable.
Public methodStatic memberStandardize(Double, Boolean)
Standardizes column data, removing the empirical standard deviation from each variable.
Public methodStatic memberStandardize(Double, Double, Boolean)
Standardizes column data, removing the empirical standard deviation from each variable.
Public methodStatic memberStandardize(Double, Double, Boolean, Double)
Standardizes column data, removing the empirical standard deviation from each variable.
Public methodStatic memberStandardize(Double, Double, Boolean, Double)
Standardizes column data, removing the empirical standard deviation from each variable.
Public methodStatic memberTies(Double)
Gets the number of ties and distinct elements in a rank vector.
Public methodStatic memberTies(Double, SortedDictionaryDouble, Int32)
Gets the number of ties and distinct elements in a rank vector.
Public methodStatic memberWhitening(Double, Double)
Computes the whitening transform for the given data, making its covariance matrix equals the identity matrix.
Public methodStatic memberWhitening(Double, Double)
Computes the whitening transform for the given data, making its covariance matrix equals the identity matrix.
Public methodStatic memberZScores(Double)
Generates the Standard Scores, also known as Z-Scores, from the given data.
Public methodStatic memberZScores(Double)
Generates the Standard Scores, also known as Z-Scores, from the given data.
Public methodStatic memberZScores(Double, Double, Double)
Generates the Standard Scores, also known as Z-Scores, from the given data.
Public methodStatic memberZScores(Double, Double, Double)
Generates the Standard Scores, also known as Z-Scores, from the given data.
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