NAME

Math::GSL::Statistics - Statistical functions

SYNOPSIS

use Math::GSL::Statistics qw /:all/;

DESCRIPTION

Here is a list of all the functions in this module :

• gsl_stats_mean($data, $stride, $n) - This function returns the arithmetic mean of the array reference $data, a dataset of length $n with stride $stride. The arithmetic mean, or sample mean, is denoted by \Hat\mu and defined as, \Hat\mu = (1/N) \sum x_i where x_i are the elements of the dataset $data. For samples drawn from a gaussian distribution the variance of \Hat\mu is \sigma^2 / N.

• gsl_stats_variance($data, $stride, $n)

• gsl_stats_sd($data, $stride, $n)

• gsl_stats_sd_m($data, $stride, $n, $mean)

• gsl_stats_variance_with_fixed_mean($data, $stride, $n, $mean)

• gsl_stats_sd_with_fixed_mean($data, $stride, $n, $mean)

• gsl_stats_tss($data, $stride, $n)

• gsl_stats_tss_m($data, $stride, $n, $mean)

• gsl_stats_absdev($data, $stride, $n)

• gsl_stats_skew($data, $stride, $n)

• gsl_stats_skew_m_sd($data, $stride, $n, $mean, $sd)

• gsl_stats_kurtosis($data, $stride, $n)

• gsl_stats_kurtosis_m_sd($data, $stride, $n, $mean, $sd)

• gsl_stats_lag1_autocorrelation($data, $stride, $n)

• gsl_stats_lag1_autocorrelation_m($data, $stride, $n, $mean)

• gsl_stats_covariance($data1, $stride1, $data2, $stride2, $n)

• gsl_stats_covariance_m($data1, $stride1, $data2, $stride2, $n, $mean1, $mean2)

• gsl_stats_correlation($data1, $stride1, $data2, $stride2, $n)

• gsl_stats_variance_m($data, $stride, $n, $mean)

• gsl_stats_absdev_m

• gsl_stats_wmean($w, $wstride, $data, $stride, $n) - This function returns the weighted mean of the dataset $data array reference with stride $stride and length $n, using the set of weights $w, which is an array reference, with stride $wstride and length $n. The weighted mean is defined as, \Hat\mu = (\sum w_i x_i) / (\sum w_i)

• gsl_stats_wvariance($w, $wstride, $data, $stride, $n)

• gsl_stats_wsd($w, $wstride, $data, $stride, $n)

• gsl_stats_wsd_m($w, $wstride, $data, $stride, $n, $wmean)

• gsl_stats_wvariance_with_fixed_mean($w, $wstride, $data, $stride, $n, $mean)

• gsl_stats_wsd_with_fixed_mean($w, $wstride, $data, $stride, $n, $mean)

• gsl_stats_wtss($w, $wstride, $data, $stride, $n)

• gsl_stats_wtss_m($w, $wstride, $data, $stride, $n, $wmean)

• gsl_stats_wabsdev($w, $wstride, $data, $stride, $n)

• gsl_stats_wabsdev_m($w, $wstride, $data, $stride, $n, $wmean)

• gsl_stats_wskew($w, $wstride, $data, $stride, $n)

• gsl_stats_wskew_m_sd($w, $wstride, $data, $stride, $n, $wmean, $wsd)

• gsl_stats_wkurtosis($w, $wstride, $data, $stride, $n)

• gsl_stats_wvariance_m($w, $wstride, $data, $stride, $n, $wmean, $wsd)

• gsl_stats_wkurtosis_m_sd($w, $wstride, $data, $stride, $n, $wmean, $wsd)

• gsl_stats_pvariance($data, $stride, $n, $data2, $stride2, $n2)

• gsl_stats_ttest

• gsl_stats_max($data, $stride, $n) - This function returns the maximum value in the $data array reference, a dataset of length $n with stride $stride. The maximum value is defined as the value of the element x_i which satisfies x_i >= x_j for all j. If you want instead to find the element with the largest absolute magnitude you will need to apply fabs or abs to your data before calling this function.

• gsl_stats_min($data, $stride, $n)

• gsl_stats_minmax($data, $stride, $n) - This function finds both the minimum and maximum values in $data, which is an array reference, in a single pass and returns them in this order.

• gsl_stats_max_index($data, $stride, $n)

• gsl_stats_min_index($data, $stride, $n)

• gsl_stats_minmax_index($data, $stride, $n)

• gsl_stats_median_from_sorted_data($data, $stride, $n)

• gsl_stats_quantile_from_sorted_data($data, $stride, $n, $f)

The following function are simply variants for int and char of the last functions:

• gsl_stats_int_mean

• gsl_stats_int_variance

• gsl_stats_int_sd

• gsl_stats_int_variance_with_fixed_mean

• gsl_stats_int_sd_with_fixed_mean

• gsl_stats_int_tss

• gsl_stats_int_tss_m

• gsl_stats_int_absdev

• gsl_stats_int_skew

• gsl_stats_int_kurtosis

• gsl_stats_int_lag1_autocorrelation

• gsl_stats_int_covariance

• gsl_stats_int_correlation

• gsl_stats_int_variance_m

• gsl_stats_int_sd_m

• gsl_stats_int_absdev_m

• gsl_stats_int_skew_m_sd

• gsl_stats_int_kurtosis_m_sd

• gsl_stats_int_lag1_autocorrelation_m

• gsl_stats_int_covariance_m

• gsl_stats_int_pvariance

• gsl_stats_int_ttest

• gsl_stats_int_max

• gsl_stats_int_min

• gsl_stats_int_minmax

• gsl_stats_int_max_index

• gsl_stats_int_min_index

• gsl_stats_int_minmax_index

• gsl_stats_int_median_from_sorted_data

• gsl_stats_int_quantile_from_sorted_data

• gsl_stats_char_mean

• gsl_stats_char_variance

• gsl_stats_char_sd

• gsl_stats_char_variance_with_fixed_mean

• gsl_stats_char_sd_with_fixed_mean

• gsl_stats_char_tss

• gsl_stats_char_tss_m

• gsl_stats_char_absdev

• gsl_stats_char_skew

• gsl_stats_char_kurtosis

• gsl_stats_char_lag1_autocorrelation

• gsl_stats_char_covariance

• gsl_stats_char_correlation

• gsl_stats_char_variance_m

• gsl_stats_char_sd_m

• gsl_stats_char_absdev_m

• gsl_stats_char_skew_m_sd

• gsl_stats_char_kurtosis_m_sd

• gsl_stats_char_lag1_autocorrelation_m

• gsl_stats_char_covariance_m

• gsl_stats_char_pvariance

• gsl_stats_char_ttest

• gsl_stats_char_max

• gsl_stats_char_min

• gsl_stats_char_minmax

• gsl_stats_char_max_index

• gsl_stats_char_min_index

• gsl_stats_char_minmax_index

• gsl_stats_char_median_from_sorted_data

• gsl_stats_char_quantile_from_sorted_data

You have to add the functions you want to use inside the qw /put_funtion_here /. You can also write use Math::GSL::Randist qw/:all/; to use all avaible functions of the module. Other tags are also avaible, here is a complete list of all tags for this module :

all

int

char

For more informations on the functions, we refer you to the GSL offcial documentation: http://www.gnu.org/software/gsl/manual/html_node/

Tip : search on google: site:http://www.gnu.org/software/gsl/manual/html_node/ name_of_the_function_you_want

AUTHORS

Jonathan Leto <jonathan@leto.net> and Thierry Moisan <thierry.moisan@gmail.com>

COPYRIGHT AND LICENSE

Copyright (C) 2008 Jonathan Leto and Thierry Moisan

This program is free software; you can redistribute it and/or modify it under the same terms as Perl itself.