Math::GSL::Statistics - Statistical functions
use Math::GSL::Statistics qw /:all/;
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 :
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
Jonathan Leto <jonathan@leto.net> and Thierry Moisan <thierry.moisan@gmail.com>
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.
