public static class Stats

<ExtensionAttribute>
Public NotInheritable Class Stats

[ExtensionAttribute]
public ref class Stats abstract sealed

[<AbstractClassAttribute>]
[<SealedAttribute>]
[<ExtensionAttribute>]
type Stats =  class end

The Stats type exposes the following members.

	Name	Description
	Autocorrelation(Double)	Gets the lag-1 auto-correlation of the elements of an array.
	Autocorrelation(NumericalVariable)	Gets the lag-1 auto-correlation of a numerical variable.
	Autocorrelation(VectorDouble)	Gets the lag-1 auto-correlation of the elements of a vector.
	Autocorrelation(Vector)	Gets the lag-1 auto-correlation of the elements of a vector.
	Autocorrelation(Double, Int32)	Gets the auto-correlation of the elements of an array.
	Autocorrelation(NumericalVariable, Int32)	Gets the auto-correlation of a numerical variable.
	Autocorrelation(VectorDouble, Int32)	Gets the auto-correlation of the elements of a vector.
	Autocorrelation(Vector, Int32)	Gets the auto-correlation of the elements of a vector.
	AverageAbsoluteDeviation	Returns the mean absolute deviation from the mean of a variable.
	BlomScores(IListDouble)	Returns the Blom scores corresponding to the specified ranks.
	BlomScores(IListInt32)	Returns the Blom scores corresponding to the specified ranks.
	CentralMoment(Double, Int32)	Returns the specified central moment of the elements of an array.
	CentralMoment(Int32, Int32)	Returns the specified central moment of the elements of an array.
	CentralMoment(NumericalVariable, Int32)	Returns the specified central moment of a numerical variable.
	CentralMoment(Vector, Int32)	Returns the specified central moment of the elements of an array.
	CentralMomentT(T, Int32)	Returns the specified central moment of the elements of an array.
	CentralMomentT(VectorT, Int32)	Returns the specified central moment of the elements of a vector.
	CoefficientOfVariation	Gets the coefficient of variation of a variable, if it exists.
	ColumnMeans(Matrix)	Returns a vector containing the means of the columns of a matrix.
	ColumnMeansT(MatrixT)	Returns a vector containing the means of the columns of a matrix.
	ColumnStandardDeviations(MatrixDouble)	Returns a vector containing the standard deviations of the columns of a matrix.
	ColumnStandardDeviations(Matrix)	Returns a vector containing the standard deviations of the columns of a matrix.
	ColumnVariances(MatrixDouble)	Returns a vector containing the variances of the columns of a matrix.
	ColumnVariances(Matrix)	Returns a vector containing the variances of the columns of a matrix.
	Correlation(Double, Double)	Gets the Pearson correlation coefficient between two sets of values.
	Correlation(NumericalVariable, NumericalVariable)	Gets the Pearson correlation coefficent between two numerical variables.
	Correlation(VectorDouble, VectorDouble)	Gets the Pearson correlation coefficient between two sets of values.
	Correlation(Vector, Vector)	Gets the Pearson correlation coefficent between two sets of values.
	CorrelationMatrix(Matrix)	Returns the correlation matrix for the columns in a matrix.
	CorrelationMatrix(NumericalVariable)	Returns the correlation matrix for an array of numerical variables.
	CorrelationMatrix(IListVectorDouble)	Returns the correlation matrix for an array of numerical variables.
	CorrelationMatrixT(MatrixT)	Returns the correlation matrix for the columns in a matrix.
	Covariance(Double, Double)	Gets the covariance between two sets of values.
	Covariance(NumericalVariable, NumericalVariable)	Gets the Pearson correlation coefficent between two numerical variables.
	Covariance(VectorDouble, VectorDouble)	Gets the covariance between two sets of values.
	Covariance(Vector, Vector)	Gets the covariance between two sets of values.
	CovarianceMatrix(Matrix)	Returns the covariance matrix for the columns in a matrix.
	CovarianceMatrix(NumericalVariable)	Returns the covariance matrix for an array of numerical variables.
	CovarianceMatrix(IListVectorDouble)	Returns the covariance matrix for an array of numerical variables.
	CovarianceMatrix(Matrix, MultipleMissingValueAction)	Returns the covariance matrix for the columns in a matrix given the column means.
	CovarianceMatrixT(MatrixT, MultipleMissingValueAction)	Returns the covariance matrix for the columns in a matrix.
	GeometricMean(Double)	Returns the geometric mean of the elements of an array.
	GeometricMean(Int32)	Returns the geometric mean of the elements of an array.
	GeometricMean(NumericalVariable)	Returns the geometric mean of the elements of a numerical variable.
	GeometricMean(VectorDouble)	Returns the geometric mean of the elements of a vector.
	GeometricMean(Vector)	Returns the geometric mean of the elements of a vector.
	GeometricMeanT(VectorT)	Returns the geometric mean of the elements of a numerical variable.
	GetKurtosisEstimate	Returns an estimate for the kurtosis of the variable.
	GetMeanEstimate	Returns an estimate for the mean of the variable.
	GetSavitskyGolayCoefficients(Int32)	Obsolete. Constructs a vector containing the coefficients of a 2nd degree Savitsky-Golay filter with the specified parameters.
	GetSavitskyGolayCoefficients(Int32, Int32)	Obsolete. Constructs a vector containing the coefficients of a Savitsky-Golay filter with the specified span and polynomial degree.
	GetSavitskyGolayCoefficients(Int32, Int32, Int32)	Obsolete. Constructs a vector containing the coefficients of a symmetrical Savitsky-Golay filter with the specified parameters.
	GetSavitskyGolayCoefficients(Int32, Int32, Int32, Int32)	Obsolete. Constructs a vector containing the coefficients of a Savitsky-Golay filter or a derivative filter with the specified parameters.
	GetSkewnessEstimate	Returns an estimate for the skewness of a variable.
	GetStandardDeviationEstimate	Returns an estimate for the standard deviation of the variable.
	HarmonicMean(Double)	Returns the harmonic mean of the elements of an array.
	HarmonicMean(Int32)	Returns the harmonic mean of the elements of an array.
	HarmonicMean(NumericalVariable)	Returns the harmonic mean of the elements of a numerical variable.
	HarmonicMean(VectorDouble)	Returns the harmonic mean of the elements of a vector.
	HarmonicMean(Vector)	Returns the harmonic mean of the elements of a vector.
	HarmonicMeanT(VectorT)	Returns the harmonic mean of the elements of a numerical variable.
	InterQuartileRange(Double)	Returns the inter-quartile range of the elements of an array.
	InterQuartileRange(Int32)	Returns the inter-quartile range of the elements of an array.
	InterQuartileRange(DateTime)	Returns the inter-quartile range of the elements of an array.
	InterQuartileRange(NumericalVariable)	Returns the inter-quartile range of the elements of a numerical variable.
	InterQuartileRange(Vector)	Returns the inter-quartile range of the elements of a vector.
	InterQuartileRangeT(VectorT)	Returns the inter-quartile range of the elements of a numerical variable.
	KendallTau(Double, Double)	Returns Kendall's tau-b correlation coefficent between two sets of values.
	KendallTau(Vector, Vector)	Returns Kendall's tau-b correlation coefficent between two sets of values.
	KendallTauT(IListT, IListT)	Returns Kendall's tau-b correlation coefficient between two sets of values.
	Kurtosis(Double)	Returns the kurtosis supplement of the elements of an array.
	Kurtosis(Int32)	Returns the kurtosis supplement of the elements of an array.
	Kurtosis(NumericalVariable)	Returns the kurtosis supplement of a numerical variable.
	Kurtosis(Vector)	Returns the kurtosis supplement of the elements of an array.
	KurtosisT(T)	Returns the kurtosis supplement of the elements of an array.
	KurtosisT(VectorT)	Returns the kurtosis supplement of the elements of an array.
	Max(DateTime)	Returns the maximum value of the elements of an array.
	Max(Double)	Returns the maximum value of the elements of an array.
	Max(Int32)	Returns the maximum value of the elements of an array.
	Max(NumericalVariable)	Returns the maximum value of the elements of a numerical variable.
	Max(Vector)	Returns the maximum value of the elements of a vector.
	MaxT(IListT)	Returns the maximum value of the elements of an array.
	MaxT(IListT, IComparerT)	Returns the maximum value of the elements of an array.
	Mean(IEnumerableDouble)	Returns the mean of the elements of a sequence.
	Mean(DateTime)	Returns the mean of the elements of an array of DateTime values.
	Mean(Double)	Returns the mean of the elements of an array.
	Mean(Int32)	Returns the mean of the elements of an array.
	Mean(NumericalVariable)	Returns the mean of the elements of a numerical variable.
	Mean(Vector)	Returns the mean of the elements of a vector.
	MeanT(VectorT)	Returns the mean of the elements of a vector.
	Median(Double)	Returns the median of the elements of an array.
	Median(Int32)	Returns the median of the elements of an array.
	Median(NumericalVariable)	Returns the median of the elements of a categorical variable.
	Median(Vector)	Returns the median of the elements of a vector.
	MedianT(IListT)	Returns the median of the elements of an array.
	MedianT(VectorT)	Returns the median of the elements of a vector.
	MedianAbsoluteDeviation	Returns the median absolute deviation of a variable.
	MidMean	Returns the mean of the data values between the 25th and 75th percentiles.
	Min(DateTime)	Returns the minimum value of the elements of an array.
	Min(Double)	Returns the minimum value of the elements of an array.
	Min(Int32)	Returns the minimum value of the elements of an array.
	Min(NumericalVariable)	Returns the minimum value of the elements of a numerical variable.
	Min(Vector)	Returns the minimum value of the elements of a vector.
	MinT(IListT)	Returns the maximum value of the elements of an array.
	MinT(IListT, IComparerT)	Returns the maximum value of the elements of an array.
	MinMax(DateTime)	Returns the minimum and maximum value of the elements of an array.
	MinMax(Double)	Returns the minimum and maximum value of the elements of an array.
	MinMax(Int32)	Returns the minimum and maximum value of the elements of an array.
	MinMax(NumericalVariable)	Returns the minimum and maximum value of the elements of a numerical variable.
	MinMax(Vector)	Returns the minimum and maximum value of the elements of a vector.
	MinMaxT(IListT)	Returns the maximum value of the elements of an array.
	MinMaxT(VectorT)	Returns the minimum and maximum value of the elements of a numerical variable.
	MinMaxT(IListT, IComparerT)	Returns the maximum value of the elements of an array.
	Moment(Int32, Int32)	Returns the specified raw moment of the elements of an array.
	Moment(Double, Int32)	Returns the specified raw moment of the elements of an array.
	Moment(NumericalVariable, Int32)	Returns the specified raw moment of a numerical variable.
	Moment(Vector, Int32)	Returns the specified raw moment of the elements of an array.
	MomentT(T, Int32)	Returns the specified raw moment of the elements of an array.
	MomentT(VectorT, Int32)	Returns the specified raw moment of the elements of an array.
	NearestCorrelationMatrix(SymmetricMatrixDouble)	Returns a positive semi-definite matrix close to a matrix.
	NearestCorrelationMatrix(SymmetricMatrix)	Returns a positive semi-definite matrix close to a matrix.
	NearestCorrelationMatrix(SymmetricMatrixDouble, NearestCorrelationMatrixAlgorithm)	Returns a positive semi-definite matrix close to a matrix.
	NearestCorrelationMatrix(SymmetricMatrix, NearestCorrelationMatrixAlgorithm)	Returns a positive semi-definite matrix close to a matrix.
	NearestCorrelationMatrix(SymmetricMatrixDouble, NearestCorrelationMatrixAlgorithm, Double, Int32)	Returns a positive semi-definite matrix close to a matrix.
	NearestCorrelationMatrix(SymmetricMatrix, NearestCorrelationMatrixAlgorithm, Double, Int32)	Returns a positive semi-definite matrix close to a matrix.
	Percentile(Double, Int32)	Gets the specified percentile.
	Percentile(NumericalVariable, Int32)	Gets the specified percentile.
	Percentile(VectorDouble, Double)	Gets the specified percentile.
	Percentile(Vector, Int32)	Gets the specified percentile.
	PercentileT(VectorT, Int32)	Gets the specified percentile.
	Percentiles(Double, Int32)	Gets the specified percentiles.
	Percentiles(NumericalVariable, Int32)	Gets the specified percentiles.
	Percentiles(VectorDouble, Int32)	Gets the specified percentiles.
	Percentiles(Vector, Int32)	Gets the specified percentiles.
	PercentilesT(VectorT, Int32)	Gets the specified percentiles.
	PopulationKurtosis(Double)	Returns the kurtosis supplement of the elements of an array.
	PopulationKurtosis(Int32)	Returns the kurtosis supplement of the elements of an array.
	PopulationKurtosis(NumericalVariable)	Returns the kurtosis supplement of a numerical variable.
	PopulationKurtosis(Vector)	Returns the kurtosis supplement of the elements of an array.
	PopulationKurtosisT(VectorT)	Returns the kurtosis supplement of the elements of an array.
	PopulationSkewness(Int32)	Returns the skewness of the elements of an array.
	PopulationSkewness(Double)	Returns the skewness of the elements of an array.
	PopulationSkewness(NumericalVariable)	Returns the skewness of a numerical variable.
	PopulationSkewness(Vector)	Returns the skewness of the elements of an array.
	PopulationSkewnessT(T)	Returns the skewness of the elements of an array.
	PopulationSkewnessT(VectorT)	Returns the skewness of the elements of an array.
	PopulationStandardDeviation(DateTime)	Returns the standard deviation of the elements of an array.
	PopulationStandardDeviation(IEnumerableDouble)	Returns the standard deviation of the elements of an array.
	PopulationStandardDeviation(Double)	Returns the standard deviation of the elements of an array.
	PopulationStandardDeviation(Int32)	Returns the standard deviation of the elements of an array.
	PopulationStandardDeviation(DateTimeVariable)	Returns the standard deviation of the elements of a numerical variable.
	PopulationStandardDeviation(NumericalVariable)	Returns the standard deviation of the elements of a numerical variable.
	PopulationStandardDeviation(VectorDateTime)	Returns the standard deviation of the elements of a numerical variable.
	PopulationStandardDeviation(Vector)	Returns the standard deviation of the elements of a vector.
	PopulationStandardDeviationT(IEnumerableT)	Returns the standard deviation of the elements of an array.
	PopulationStandardDeviationT(T)	Returns the standard deviation of the elements of an array.
	PopulationStandardDeviationT(VectorT)	Returns the standard deviation of the elements of a vector.
	PopulationVariance(IEnumerableDouble)	Returns the variance of the elements of an array.
	PopulationVariance(Double)	Returns the variance of the elements of an array.
	PopulationVariance(Int32)	Returns the variance of the elements of an array.
	PopulationVariance(NumericalVariable)	Returns the variance of the elements of a numerical variable.
	PopulationVariance(Vector)	Returns the variance of the elements of a vector.
	PopulationVarianceT(IEnumerableT)	Returns the variance of the elements of an array.
	PopulationVarianceT(T)	Returns the variance of the elements of an array.
	PopulationVarianceT(VectorT)	Returns the variance of the elements of a vector.
	ProcessMissingValues(Double, MissingValueAction)	Applies the specified action to the missing values in the values.
	ProcessMissingValues(Double, MissingValueAction)	Applies the specified action to the missing values in the data.
	ProcessMissingValues(VectorDouble, MissingValueAction)	Applies the specified action to the missing values in the values.
	ProcessMissingValues(Vector, MissingValueAction)	Applies the specified action to the missing values in the data.
	ProcessMissingValues(Double, MissingValueAction, Double)	Applies the specified action to the missing values in the values.
	ProcessMissingValues(Double, MissingValueAction, Double)	Applies the specified action to the missing values in the data.
	ProcessMissingValues(VectorDouble, MissingValueAction, Double)	Applies the specified action to the missing values in the values.
	ProcessMissingValues(Vector, MissingValueAction, Double)	Applies the specified action to the missing values in the data.
	ProcessMissingValues(Double, Double, MissingValueAction, Double)	Applies the specified action to the missing values in the values.
	ProcessMissingValues(Double, Double, MissingValueAction, Double)	Applies the specified action to the missing values in the data.
	ProcessMissingValues(VectorDouble, Double, MissingValueAction, Double)	Applies the specified action to the missing values in the values.
	ProcessMissingValues(Vector, Double, MissingValueAction, Double)	Applies the specified action to the missing values in the data.
	Quantile(Double, Double)	Gets the specified quantile.
	Quantile(VectorDouble, Double)	Gets the specified quantile.
	QuantileT(VectorT, Double)	Gets the specified quantile.
	Quantiles(Double, Double)	Gets the specified quantiles.
	Quantiles(VectorDouble, Double)	Gets the specified quantiles.
	QuantilesT(VectorT, Double)	Gets the specified quantiles.
	Range(DateTime)	Returns the range of the elements of an array.
	Range(Double)	Returns the range of the elements of an array.
	Range(Int32)	Returns the range of the elements of an array.
	Range(NumericalVariable)	Returns the range of the elements of a numerical variable.
	Range(VectorDouble)	Returns the range of the elements of a vector.
	Range(Vector)	Returns the range of the elements of a vector.
	RangeT(T)	Returns the range of the elements of an array.
	RangeT(VectorT)	Returns the range of the elements of a numerical variable.
	RankCorrelation(Double, Double)	Gets the Spearman rank correlation coefficient between two sets of values.
	RankCorrelation(NumericalVariable, NumericalVariable)	Gets the Spearman rank correlation coefficent between two numerical variables.
	RankCorrelation(VectorDouble, VectorDouble)	Gets the Spearman rank correlation coefficient between two sets of values.
	RankCorrelation(Vector, Vector)	Gets the Spearman rank correlation coefficent between two sets of values.
	Ranks(DateTime)	Returns the ranks of the observations.
	Ranks(Double)	Returns the ranks of the observations.
	Ranks(VectorDouble)	Returns the ranks of the observations.
	Ranks(Vector)	Returns the ranks of the observations.
	Ranks(DateTime, RankTiebreaker, TimeSpan)	Returns the ranks of the observations.
	Ranks(Double, RankTiebreaker, Double)	Returns the ranks of the observations.
	Ranks(DateTime, RankTiebreaker, TimeSpan)	Returns the ranks of the observations.
	Ranks(Double, RankTiebreaker, Double)	Returns the ranks of the observations.
	Ranks(VectorDouble, RankTiebreaker, Double)	Returns the ranks of the observations.
	Ranks(Vector, RankTiebreaker, Double)	Returns the ranks of the observations.
	RootMeanSquare(DateTime)	Returns the root-mean-square of the elements of an array.
	RootMeanSquare(Double)	Returns the root-mean-square of the elements of an array.
	RootMeanSquare(Int32)	Returns the root-mean-square of the elements of an array.
	RootMeanSquare(NumericalVariable)	Returns the root-mean-square of the elements of a numerical variable.
	RootMeanSquare(VectorDouble)	Returns the root-mean-square of the elements of a vector.
	RootMeanSquare(Vector)	Returns the root-mean-square of the elements of a vector.
	RowMeans(Matrix)	Returns a vector containing the means of the rows of a matrix.
	RowMeansT(MatrixT)	Returns a vector containing the means of the rows of a matrix.
	RowStandardDeviations(MatrixDouble)	Returns a vector containing the standard deviations of the rows of a matrix.
	RowStandardDeviations(Matrix)	Returns a vector containing the standard deviations of the rows of a matrix.
	RowVariances(MatrixDouble)	Returns a vector containing the variances of the rows of a matrix.
	RowVariances(Matrix)	Returns a vector containing the variances of the rows of a matrix.
	Skewness(Double)	Returns the skewness of the elements of an array.
	Skewness(Int32)	Returns the skewness of the elements of an array.
	Skewness(NumericalVariable)	Returns the skewness of a numerical variable.
	Skewness(Vector)	Returns the skewness of the elements of an array.
	SkewnessT(T)	Returns the skewness of the elements of an array.
	SkewnessT(VectorT)	Returns the skewness of the elements of an array.
	StandardDeviation(IEnumerableDouble)	Returns the standard deviation of the elements of an array.
	StandardDeviation(DateTime)	Returns the standard deviation of the elements of an array.
	StandardDeviation(Double)	Returns the standard deviation of the elements of an array.
	StandardDeviation(Int32)	Returns the standard deviation of the elements of an array.
	StandardDeviation(DateTimeVariable)	Returns the standard deviation of the elements of a numerical variable.
	StandardDeviation(NumericalVariable)	Returns the standard deviation of the elements of a numerical variable.
	StandardDeviation(VectorDateTime)	Returns the standard deviation of the elements of a numerical variable.
	StandardDeviation(VectorDouble)	Returns the standard deviation of the elements of a vector.
	StandardDeviation(Vector)	Returns the standard deviation of the elements of a vector.
	StandardDeviationT(VectorT)	Returns the standard deviation of the elements of a vector.
	Sum(IEnumerableDouble)	Returns the sum of the elements of a sequence.
	Sum(Double)	Returns the sum of the elements of an array.
	Sum(Int32)	Returns the sum of the elements of an array.
	Sum(NumericalVariable)	Returns the sum of the observations in a NumericalVariable.
	Sum(Vector)	Returns the sum of the elements of an array.
	SumT(VectorT)	Returns the sum of the observations in a VectorT.
	SumOfSquares(IEnumerableDouble)	Returns the sum of the squares of the elements of an array.
	SumOfSquares(Double)	Returns the sum of the squares of the elements of an array.
	SumOfSquares(Int32)	Returns the sum of the squares of the elements of an array.
	SumOfSquares(NumericalVariable)	Returns the sum of the squares of the observations in a NumericalVariable.
	SumOfSquares(Vector)	Returns the sum of the squares of the elements of an array.
	SumOfSquaresT(VectorT)	Returns the sum of the squares of the observations in a VectorT.
	TrimmedMean(Double, Double)	Returns the trimmed mean of the elements of an array.
	TrimmedMean(DateTime, Double)	Returns the trimmed mean of the elements of an array of DateTime values.
	TrimmedMean(Int32, Double)	Returns the trimmed mean of the elements of an array.
	TrimmedMean(NumericalVariable, Double)	Returns the trimmed mean of the elements of a numerical variable.
	TrimmedMean(VectorDouble, Double)	Returns the trimmed mean of the elements of a vector.
	TrimmedMean(Vector, Double)	Returns the trimmed mean of the elements of a vector.
	TrimmedMeanT(T, Double)	Returns the trimmed mean of the elements of a numerical variable.
	TrimmedMeanT(VectorT, Double)	Returns the trimmed mean of the elements of a numerical variable.
	TukeyScores(IListDouble)	Returns the Tukey scores corresponding to the specified ranks.
	TukeyScores(IListInt32)	Returns the Tukey scores corresponding to the specified ranks.
	VanDerWaerdenScores(IListDouble)	Returns the van der Waerden scores corresponding to the specified ranks.
	VanDerWaerdenScores(IListInt32)	Returns the van der Waerden scores corresponding to the specified ranks.
	Variance(IEnumerableDouble)	Returns the variance of the elements of an array.
	Variance(Double)	Returns the variance of the elements of an array.
	Variance(Int32)	Returns the variance of the elements of an array.
	Variance(NumericalVariable)	Returns the variance of the elements of a numerical variable.
	Variance(Vector)	Returns the variance of the elements of a vector.
	VarianceT(IEnumerableT)	Returns the variance of the elements of a sequence.
	VarianceT(T)	Returns the variance of the elements of an array.
	VarianceT(VectorT)	Returns the variance of the elements of a vector.
	WeightedMean(VectorDouble, VectorDouble)	Returns the mean of the variable with observations weighted by the specified vector.
	WeightedMeanT(VectorT, VectorT)	Returns the mean of the variable with observations weighted by the specified vector.
	WeightedStandardDeviation(VectorDouble, VectorDouble)	Returns the standard deviation of the variable with observations weighted by the specified vector.
	WeightedStandardDeviationT(VectorT, VectorT)	Returns the standard deviation of the variable with observations weighted by the specified vector.
	WinsorizedMean	Returns the Winsorized mean of the variable..

Use the Stats class to do quick calculations on your values without loading it into one of the statistical variable classes. If you need to calculate multiple properties of your values, it is much more efficient to load the values into a variable first, and use the properties and methods of the variable class to obtain your results.

Numerical Libraries

Reference