= distribution
* https://github.com/clbustos/distribution
== DESCRIPTION:
Statistical Distributions library. Includes Normal univariate and bivariate, T, F, Chi Square, Binomial, Hypergeometric, Exponential and Poisson.
Uses Ruby by default and C (statistics2/GSL) or Java extensions where available.
Includes code from statistics2 on Normal, T, F and Chi Square ruby code [http://blade.nagaokaut.ac.jp/~sinara/ruby/math/statistics2]
== FEATURES/PROBLEMS:
* Very fast ruby 1.8.7/1.9.+ implementation, with improved method to calculate factorials and others common functions
* All methods tested on several ranges. See spec/
* On Jruby and Rubinius, BivariateNormal returns incorrect pdf
* Ruby t distribution's cdf can't calculate fractional df. Install gsl, for now.
== API structure
Distribution::<name>.(cdf|pdf|p_value|rng)
On discrete distributions, exact Ruby implementations of pdf, cdf and p_value could be provided, using
Distribution::<name>.exact_(cdf|pdf|p_value)
module Distribution::Shorthand provides (you guess?) shortands method to call all methods
<Distribution shortname>_(cdf|pdf|p|r)
On discrete distributions, exact cdf, pdf and p_value are
<Distribution shortname>_(ecdf|epdf|ep)
Shortnames for distributions:
* Normal: norm
* Bivariate Normal: bnor
* T: tdist
* F: fdist
* Chi Square: chisq
* Binomial: bino
* Hypergeometric: hypg
* Exponential: expo
* Poisson: pois
For example
Distribution::T.cdf
could be called after including Distribution::Shorthand
tdist_cdf
== SYNOPSIS:
# Returns Gaussian PDF for x
pdf=Distribution::Normal.pdf(x)
# Returns Gaussian CDF for x
cdf=Distribution::Normal.cdf(x)
# Returns inverse CDF (or p-value) for x
pv =Distribution::Normal.p_value(x)
== REQUIREMENTS:
I try to provide a Ruby version for each method. To increase (notably!) the speed, please install
* Ruby 1.8-1.9: gsl or statistics2
* Java: Apache Math (not yet implemented)
== INSTALL:
gem install distribution
To speep up
gem install gsl
gem install statistics
== DEVELOPERS:
After checking out the source, run:
$ rake newb
This task will install any missing dependencies, run the tests/specs,
and generate the RDoc.
If you want to provide a new distribution, /lib/distribution run
$ distribution --new your_distribution
This should create the main distribution file, the directory with ruby and gsl engines and the rspec on /spec directory.
== LICENSE:
GPL V2
* https://github.com/clbustos/distribution
== DESCRIPTION:
Statistical Distributions library. Includes Normal univariate and bivariate, T, F, Chi Square, Binomial, Hypergeometric, Exponential and Poisson.
Uses Ruby by default and C (statistics2/GSL) or Java extensions where available.
Includes code from statistics2 on Normal, T, F and Chi Square ruby code [http://blade.nagaokaut.ac.jp/~sinara/ruby/math/statistics2]
== FEATURES/PROBLEMS:
* Very fast ruby 1.8.7/1.9.+ implementation, with improved method to calculate factorials and others common functions
* All methods tested on several ranges. See spec/
* On Jruby and Rubinius, BivariateNormal returns incorrect pdf
* Ruby t distribution's cdf can't calculate fractional df. Install gsl, for now.
== API structure
Distribution::<name>.(cdf|pdf|p_value|rng)
On discrete distributions, exact Ruby implementations of pdf, cdf and p_value could be provided, using
Distribution::<name>.exact_(cdf|pdf|p_value)
module Distribution::Shorthand provides (you guess?) shortands method to call all methods
<Distribution shortname>_(cdf|pdf|p|r)
On discrete distributions, exact cdf, pdf and p_value are
<Distribution shortname>_(ecdf|epdf|ep)
Shortnames for distributions:
* Normal: norm
* Bivariate Normal: bnor
* T: tdist
* F: fdist
* Chi Square: chisq
* Binomial: bino
* Hypergeometric: hypg
* Exponential: expo
* Poisson: pois
For example
Distribution::T.cdf
could be called after including Distribution::Shorthand
tdist_cdf
== SYNOPSIS:
# Returns Gaussian PDF for x
pdf=Distribution::Normal.pdf(x)
# Returns Gaussian CDF for x
cdf=Distribution::Normal.cdf(x)
# Returns inverse CDF (or p-value) for x
pv =Distribution::Normal.p_value(x)
== REQUIREMENTS:
I try to provide a Ruby version for each method. To increase (notably!) the speed, please install
* Ruby 1.8-1.9: gsl or statistics2
* Java: Apache Math (not yet implemented)
== INSTALL:
gem install distribution
To speep up
gem install gsl
gem install statistics
== DEVELOPERS:
After checking out the source, run:
$ rake newb
This task will install any missing dependencies, run the tests/specs,
and generate the RDoc.
If you want to provide a new distribution, /lib/distribution run
$ distribution --new your_distribution
This should create the main distribution file, the directory with ruby and gsl engines and the rspec on /spec directory.
== LICENSE:
GPL V2