hmatrix-gsl-stats-0.1.2.9: GSL Statistics interface

Portability uses ffi provisional haskell.vivian.mcphail gmail com

Numeric.GSL.Statistics

Description

GSL statistics functions

Synopsis

# Documentation

the mean of the elements of a vector

the sample variance

the sample variance given the precomputed mean

the population variance given the a priori mean

the sample standard deviation

the sample standard deviation given the precomputed mean

the population standard deviation given the a priori mean

the total sum of squares about the mean

the total sum of squares about the precomputed mean

the absolute deviation from the mean

the absolute deviation from the precomputed mean

the skewness of the data (asymmetry of tails)

the skewness of the data (asymmetry of tails) with precomputed mean and sd

the kurtosis of the data (sharpness of peak relative to width)

the kurtosis of the data (sharpness of peak relative to width) with precomputed mean and sd

Arguments

 :: Vector Double weights -> Vector Double dataset -> Double

the weighted mean of the elements of a vector

the weighted sample variance

the weighted sample variance given the precomputed mean

the weighted population variance given the a priori mean

the weighted sample standard deviation

the weighted sample standard deviation given the precomputed mean

the weighted population standard deviation given the a priori mean

the weighted total sum of squares about the mean

the weighted total sum of squares about the precomputed mean

the weighted absolute deviation from the mean

the weighted absolute deviation from the precomputed mean

the weighted skewness of the data (asymmetry of tails)

the weighted skewness of the data (asymmetry of tails) with precomputed mean and sd

the weighted kurtosis of the data (sharpness of peak relative to width)

the weighted kurtosis of the data (sharpness of peak relative to width) with precomputed mean and sd

the lag-1 autocorrelation of the data

the covariance of two datasets of the same length

the covariance of two datasets of the same length

the Pearson correlation of two datasets of the same length

the median value of the dataset, which must be sorted

Arguments

 :: Double the desired quantile from [0..1] -> Vector Double the dataset -> Double

the quantile value of the dataset, which must be sorted