Tools Class 
Namespace: Accord.Statistics
The Tools type exposes the following members.
Name  Description  

Center(Double, Boolean) 
Centers column data, subtracting the empirical mean from each variable.
 
Center(Double, Double) 
Centers an observation, subtracting the empirical
mean from each element in the observation vector.
 
Center(Double, Boolean) 
Centers column data, subtracting the empirical mean from each variable.
 
Center(Double, Double, Boolean) 
Centers column data, subtracting the empirical mean from each variable.
 
Center(Double, Double, Double) 
Centers an observation, subtracting the empirical
mean from each element in the observation vector.
 
Center(Double, Double, Boolean)  Centers column data, subtracting the empirical mean from each variable.  
Determination 
Gets the coefficient of determination, as known as the RSquared (R²)
 
Distance 
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.
 
Expand(Int32)  Obsolete.
Obsolete. Please use OneHot(Int32) instead.
 
Expand(Int32, Int32)  Obsolete.
Obsolete. Please use OneHot(Int32) instead.
 
Expand(Int32, Double, Double)  Obsolete.
Obsolete. Please use OneHot(Int32) instead.
 
Expand(Int32, Int32, Int32)  Obsolete.
Obsolete. Please use Expand(Int32, Int32, Int32) instead.
 
Expand(Int32, Int32, Double, Double)  Obsolete.
Obsolete. Please use OneHot(Int32) instead.
 
Expand(Int32, Int32, Int32, Int32)  Obsolete.
Obsolete. Please use Expand(Int32, Int32, Int32) instead.
 
FitTDistribution(Double, Double) 
Creates a new distribution that has been fit to a given set of observations.
 
FitTDistribution(Double, Double) 
Creates a new distribution that has been fit to a given set of observations.
 
FitTDistribution, TOptions(Double, TOptions, Double) 
Creates a new distribution that has been fit to a given set of observations.
 
FitTDistribution, TOptions(Double, TOptions, Double) 
Creates a new distribution that has been fit to a given set of observations.
 
FitNewTDistribution, TObservations(TDistribution, TObservations, Double) 
Creates a new distribution that has been fit to a given set of observations.
 
FitNewTDistribution, TObservations, TOptions(TDistribution, TObservations, TOptions, Double) 
Creates a new distribution that has been fit to a given set of observations.
 
Group  Obsolete.
Obsolete. Please use Summarize(Int32, Int32, Int32) instead.
 
InnerFence 
Creates Tukey's box plot inner fence.
 
OuterFence 
Creates Tukey's box plot outer fence.
 
Proportions(Int32, Int32)  Obsolete.
Obsolete. Please use GetRatio(Int32, Int32) instead.
 
Proportions(Int32, Int32, Int32)  Obsolete.
Obsolete. Please use GetRatio(Int32, Int32, Int32) instead.
 
Random  Obsolete.
Obsolete. Please use Sample(Int32) instead.
 
RandomCovariance 
Generates a random Covariance(Double, Double, Boolean) matrix.
 
RandomGroups(Int32, Double)  Obsolete.
Obsolete. Please use Random(Int32, Double) instead.
 
RandomGroups(Int32, Int32)  Obsolete.
Obsolete. Please use Random(Int32, Int32) instead.
 
RandomGroups(Int32, Int32, Int32)  Obsolete.
Obsolete. Please use Random(Int32, Int32, Int32) instead.
 
RandomSample  Obsolete.
Obsolete. Please use Sample(Int32, Int32) instead.
 
Rank(Double, Boolean, Boolean) 
Gets the rank of a sample, often used with order statistics.
 
Rank(Double, Boolean, Boolean, Boolean) 
Gets the rank of a sample, often used with order statistics.
 
ShuffleT(IListT)  Obsolete.
Obsolete. Please use ShuffleT(IListT) instead.
 
ShuffleT(T)  Obsolete.
Obsolete. Please use ShuffleT(T) instead.
 
Standardize(Double, Boolean) 
Standardizes column data, removing the empirical standard deviation from each variable.
 
Standardize(Double, Boolean) 
Standardizes column data, removing the empirical standard deviation from each variable.
 
Standardize(Double, Boolean) 
Standardizes column data, removing the empirical standard deviation from each variable.
 
Standardize(Double, Double, Boolean) 
Standardizes column data, removing the empirical standard deviation from each variable.
 
Standardize(Double, Double, Boolean, Double) 
Standardizes column data, removing the empirical standard deviation from each variable.
 
Standardize(Double, Double, Boolean, Double) 
Standardizes column data, removing the empirical standard deviation from each variable.
 
Ties(Double) 
Gets the number of ties and distinct elements in a rank vector.
 
Ties(Double, SortedDictionaryDouble, Int32) 
Gets the number of ties and distinct elements in a rank vector.
 
Whitening(Double, Double) 
Computes the whitening transform for the given data, making
its covariance matrix equals the identity matrix.
 
Whitening(Double, Double) 
Computes the whitening transform for the given data, making
its covariance matrix equals the identity matrix.
 
ZScores(Double) 
Generates the Standard Scores, also known as ZScores, from the given data.
 
ZScores(Double) 
Generates the Standard Scores, also known as ZScores, from the given data.
 
ZScores(Double, Double, Double) 
Generates the Standard Scores, also known as ZScores, from the given data.
 
ZScores(Double, Double, Double) 
Generates the Standard Scores, also known as ZScores, from the given data.
