Math::GSL::CDF - Cumulative Distribution Functions
use Math::GSL::CDF qw/:all/;
my $x = gsl_cdf_gaussian_Pinv($P, $sigma);
use Math::GSL::CDF qw/:beta/;
print gsl_cdf_beta_P(1,2,3) . "\n";
These functions compute the cumulative distribution functions
P(x), Q(x) and their inverses for the named distributions.
Here is a list of all the functions included in this module :
- gsl_cdf_ugaussian_P($x)
- gsl_cdf_ugaussian_Q($x)
- gsl_cdf_ugaussian_Pinv($P)
- gsl_cdf_ugaussian_Qinv($Q)
- These functions compute the cumulative distribution functions P(x), Q(x)
and their inverses for the unit Gaussian distribution.
- gsl_cdf_gaussian_P($x,
$sigma)
- gsl_cdf_gaussian_Q($x,
$sigma)
- gsl_cdf_gaussian_Pinv($P,
$sigma)
- gsl_cdf_gaussian_Qinv($Q,
$sigma)
- These functions compute the cumulative distribution functions P(x), Q(x)
and their inverses for the Gaussian distribution with standard deviation
$sigma.
- gsl_cdf_gamma_P($x,
$a, $b)
- gsl_cdf_gamma_Q($x,
$a, $b)
- gsl_cdf_gamma_Pinv($P,
$a, $b)
- gsl_cdf_gamma_Qinv($Q,
$a, $b)
- These functions compute the cumulative distribution functions P(x), Q(x)
and their inverses for the gamma distribution with parameters
$a and $b.
- gsl_cdf_cauchy_P($x,
$a)
- gsl_cdf_cauchy_Q($x,
$a)
- gsl_cdf_cauchy_Pinv($P,
$a)
- gsl_cdf_cauchy_Qinv($Q,
$a)
- These functions compute the cumulative distribution functions P(x), Q(x)
and their inverses for the Cauchy distribution with scale parameter
$a.
- gsl_cdf_laplace_P($x,
$a)
- gsl_cdf_laplace_Q($x,
$a)
- gsl_cdf_laplace_Pinv($P,
$a)
- gsl_cdf_laplace_Qinv($Q,
$a)
- These functions compute the cumulative distribution functions P(x), Q(x)
and their inverses for the Laplace distribution with width
$a.
- gsl_cdf_rayleigh_P($x,
$sigma)
- gsl_cdf_rayleigh_Q($x,
$sigma)
- gsl_cdf_rayleigh_Pinv($P,
$sigma)
- gsl_cdf_rayleigh_Qinv($Q,
$sigma)
- These functions compute the cumulative distribution functions P(x), Q(x)
and their inverses for the Rayleigh distribution with scale parameter
$sigma.
- gsl_cdf_chisq_P($x,
$nu)
- gsl_cdf_chisq_Q($x,
$nu)
- gsl_cdf_chisq_Pinv($P,
$nu)
- gsl_cdf_chisq_Qinv($Q,
$nu)
- These functions compute the cumulative distribution functions P(x), Q(x)
and their inverses for the chi-squared distribution with
$nu degrees of freedom.
- gsl_cdf_exponential_P($x,
$mu)
- gsl_cdf_exponential_Q($x,
$mu)
- gsl_cdf_exponential_Pinv($P,
$mu)
- gsl_cdf_exponential_Qinv($Q,
$mu)
- These functions compute the cumulative distribution functions P(x), Q(x)
and their inverses for the Laplace distribution with width
$a.
- gsl_cdf_exppow_P($x,
$a, $b)
- gsl_cdf_exppow_Q($x,
$a, $b)
- These functions compute the cumulative distribution functions P(x), Q(x)
for the exponential power distribution with parameters
$a and $b.
- gsl_cdf_tdist_P($x,
$nu)
- gsl_cdf_tdist_Q($x,
$nu)
- gsl_cdf_tdist_Pinv($P,
$nu)
- gsl_cdf_tdist_Qinv($Q,
$nu)
- These functions compute the cumulative distribution functions P(x), Q(x)
and their inverses for the t-distribution with $nu
degrees of freedom.
- gsl_cdf_fdist_P($x,
$nu1, $nu2)
- gsl_cdf_fdist_Q($x,
$nu1, $nu2)
- gsl_cdf_fdist_Pinv($P,
$nu1, $nu2)
- gsl_cdf_fdist_Qinv($Q,
$nu1, $nu2)
- These functions compute the cumulative distribution functions P(x), Q(x)
and their inverses for the F-distribution with
$nu1 and $nu2 degrees of
freedom.
- gsl_cdf_beta_P($x,
$a, $b)
- gsl_cdf_beta_Q($x,
$a, $b)
- gsl_cdf_beta_Pinv($P,
$a, $b)
- gsl_cdf_beta_Qinv($Q,
$a, $b)
- These functions compute the cumulative distribution functions P(x), Q(x)
and their inverses for the beta distribution with parameters
$a and $b.
- gsl_cdf_flat_P($x,
$a, $b)
- gsl_cdf_flat_Q($x,
$a, $b)
- gsl_cdf_flat_Pinv($P,
$a, $b)
- gsl_cdf_flat_Qinv($Q,
$a, $b)
- These functions compute the cumulative distribution functions P(x), Q(x)
and their inverses for a uniform distribution from
$a to $b.
- gsl_cdf_lognormal_P($x,
$zeta, $sigma)
- gsl_cdf_lognormal_Q($x,
$zeta, $sigma)
- gsl_cdf_lognormal_Pinv($P,
$zeta, $sigma)
- gsl_cdf_lognormal_Qinv($Q,
$zeta, $sigma)
- These functions compute the cumulative distribution functions P(x), Q(x)
and their inverses for the lognormal distribution with parameters
$zeta and $sigma.
- gsl_cdf_gumbel1_P($x,
$a, $b)
- gsl_cdf_gumbel1_Q($x,
$a, $b)
- gsl_cdf_gumbel1_Pinv($P,
$a, $b)
- gsl_cdf_gumbel1_Qinv($Q,
$a, $b)
- These functions compute the cumulative distribution functions P(x), Q(x)
and their inverses for the Type-1 Gumbel distribution with parameters
$a and $b.
- gsl_cdf_gumbel2_P($x,
$a, $b)
- gsl_cdf_gumbel2_Q($x,
$a, $b)
- gsl_cdf_gumbel2_Pinv($P,
$a, $b)
- gsl_cdf_gumbel2_Qinv($Q,
$a, $b)
- These functions compute the cumulative distribution functions P(x), Q(x)
and their inverses for the Type-2 Gumbel distribution with parameters
$a and $b.
- gsl_cdf_weibull_P($x,
$a, $b)
- gsl_cdf_weibull_Q($x,
$a, $b)
- gsl_cdf_weibull_Pinv($P,
$a, $b)
- gsl_cdf_weibull_Qinv($Q,
$a, $b)
- These functions compute the cumulative distribution functions P(x), Q(x)
and their inverses for the Type-1 Gumbel distribution with parameters
$a and $b.
- gsl_cdf_pareto_P($x,
$a, $b)
- gsl_cdf_pareto_Q($x,
$a, $b)
- gsl_cdf_pareto_Pinv($P,
$a, $b)
- gsl_cdf_pareto_Qinv($Q,
$a, $b)
- These functions compute the cumulative distribution functions P(x), Q(x)
and their inverses for the Pareto distribution with exponent
$a and scale $b.
- gsl_cdf_logistic_P($x,
$a)
- gsl_cdf_logistic_Q($x,
$a)
- gsl_cdf_logistic_Pinv($P,
$a)
- gsl_cdf_logistic_Qinv($Q,
$a)
- These functions compute the cumulative distribution functions P(x), Q(x)
and their inverses for the logistic distribution with scale parameter
a.
- gsl_cdf_binomial_P($k,
$p, $n)
- gsl_cdf_binomial_Q($k,
$p, $n)
- These functions compute the cumulative distribution functions P(k), Q(k)
for the binomial distribution with parameters $p
and $n.
- gsl_cdf_poisson_P($k,
$mu)
- gsl_cdf_poisson_Q($k,
$mu)
- These functions compute the cumulative distribution functions P(k), Q(k)
for the Poisson distribution with parameter
$mu.
- gsl_cdf_geometric_P($k,
$p)
- gsl_cdf_geometric_Q($k,
$p)
- These functions compute the cumulative distribution functions P(k), Q(k)
for the geometric distribution with parameter
$p.
- gsl_cdf_negative_binomial_P($k,
$p, $n)
- gsl_cdf_negative_binomial_Q($k,
$p, $n)
- These functions compute the cumulative distribution functions P(k), Q(k)
for the negative binomial distribution with parameters
$p and $n.
- gsl_cdf_pascal_P($k,
$p, $n)
- gsl_cdf_pascal_Q($k,
$p, $n)
- These functions compute the cumulative distribution functions P(k), Q(k)
for the Pascal distribution with parameters $p and
$n.
- gsl_cdf_hypergeometric_P($k,
$n1, $n2, $t)
- gsl_cdf_hypergeometric_Q($k,
$n1, $n2, $t)
- These functions compute the cumulative distribution functions P(k), Q(k)
for the hypergeometric distribution with parameters
$n1, $n2 and
$t.
To import specific functions, list them in the use line. To import
all function exportable by Math::GSL::CDF do
use Math::GSL::CDF qw/:all/
This is the list of available import tags:
- geometric
- tdist
- ugaussian
- rayleigh
- pascal
- exponential
- gumbel2
- gumbel1
- exppow
- logistic
- weibull
- gaussian
- poisson
- beta
- binomial
- laplace
- lognormal
- cauchy
- fdist
- chisq
- gamma
- hypergeometric
- negative
- pareto
- flat
For example the beta tag contains theses functions :
gsl_cdf_beta_P, gsl_cdf_beta_Q, gsl_cdf_beta_Pinv, gsl_cdf_beta_Qinv .
For more information on the functions, we refer you to the GSL
offcial documentation:
<http://www.gnu.org/software/gsl/manual/html_node/>
Jonathan "Duke" Leto <jonathan@leto.net> and
Thierry Moisan <thierry.moisan@gmail.com>
Copyright (C) 2008-2020 Jonathan "Duke" Leto and Thierry
Moisan
This program is free software; you can redistribute it and/or
modify it under the same terms as Perl itself.