# Probability distributions library in Ruby **URL:** \ **Category:** Ruby\ **Created:** [April 12, 2007, 11:56pm UTC](https://www.ruby-forum.com/t/probability-distributions-library-in-ruby/91872 "2007-04-12T23:56:19Z")\ **Posts on this page:** 7\ **Page:** 1
**Author:** ![Libra](https://www.ruby-forum.com/letter_avatar_proxy/v4/letter/l/ed655f/32.png) [@Libra](https://www.ruby-forum.com/u/Libra)\ **Post date:** [April 12, 2007, 11:56pm UTC](https://www.ruby-forum.com/t/probability-distributions-library-in-ruby/91872/1 "2007-04-12T23:56:19Z")
Hello, I would extract some numbers according to a given probability distribution (at least, Normal, Exponential, Poisson and Bernoulli). Do you know if a similar library already exists in Ruby? I only found pseudo-random number generator. TIA Libra ---
**Author:** ![Libra](https://www.ruby-forum.com/letter_avatar_proxy/v4/letter/l/ed655f/32.png) [@Libra](https://www.ruby-forum.com/u/Libra)\ **Post date:** [April 13, 2007, 12:35am UTC](https://www.ruby-forum.com/t/probability-distributions-library-in-ruby/91872/2 "2007-04-13T00:35:22Z")
If you don’t find any library, you can always write your own using the technique outlined in section 1.3 of this paper. [http://eeyore.ucdavis.edu/stat141/RNG.pdf](http://eeyore.ucdavis.edu/stat141/RNG.pdf) Basically given the CDF F of some distribution (say, Poisson), you can generate random numbers from the Poisson distribution by doing: u = rand # uniformely generated random number y = Finv(u) -Szymon ---
**Author:** ![Libra](https://www.ruby-forum.com/letter_avatar_proxy/v4/letter/l/ed655f/32.png) [@Libra](https://www.ruby-forum.com/u/Libra)\ **Post date:** [April 13, 2007, 2:36am UTC](https://www.ruby-forum.com/t/probability-distributions-library-in-ruby/91872/3 "2007-04-13T02:36:30Z")
On 13 Apr 2007, at 06:55, Libra wrote: > Libra > If you are comfortable with R, you can use RSRuby (http:// > web.kuicr.kyoto-u.ac.jp/~alexg/rsruby/) to generate numbers from any > its distribution functions. For example, extracting 10 numbers from a > normal distribution with mean 0: [alexg@powerbook]/Users/alexg(1): irb -rubygems irb(main):001:0\> require ‘rsruby’ =\> true irb(main):002:0\> r = RSRuby.instance =\> #RSRuby:0x1c1510 irb(main):003:0\> r.rnorm(10) =\> [-0.418488870801272, 3.8442920287686, -2.23915973195997, -1.1852964455658, 0.292187794718865, -0.0538355720349994, -0.682675725085902, -0.179593328583021, 0.617238096715829, -0.353627801112474] The default R stats package has the following distributions built in and you can use any R library to add more (I couldn’t see Bernoulli in this list, but maybe it has an alternative name?): Beta(stats) The Beta Distribution Binomial(stats) The Binomial Distribution Cauchy(stats) The Cauchy Distribution Chisquare(stats) The (non-central) Chi-Squared Distribution Exponential(stats) The Exponential Distribution FDist(stats) The F Distribution GammaDist(stats) The Gamma Distribution Geometric(stats) The Geometric Distribution Hypergeometric(stats) The Hypergeometric Distribution Logistic(stats) The Logistic Distribution Lognormal(stats) The Log Normal Distribution Multinomial(stats) The Multinomial Distribution NegBinomial(stats) The Negative Binomial Distribution Normal(stats) The Normal Distribution Poisson(stats) The Poisson Distribution SignRank(stats) Distribution of the Wilcoxon Signed Rank Statistic TDist(stats) The Student t Distribution Tukey(stats) The Studentized Range Distribution Uniform(stats) The Uniform Distribution Weibull(stats) The Weibull Distribution Wilcoxon(stats) Distribution of the Wilcoxon Rank Sum Statistic ecdf(stats) Empirical Cumulative Distribution Function survreg.distributions(survival) Parametric Survival Distributions Alex G. Bioinformatics Center Kyoto University ---
**Author:** ![Libra](https://www.ruby-forum.com/letter_avatar_proxy/v4/letter/l/ed655f/32.png) [@Libra](https://www.ruby-forum.com/u/Libra)\ **Post date:** [April 15, 2007, 2:16pm UTC](https://www.ruby-forum.com/t/probability-distributions-library-in-ruby/91872/4 "2007-04-15T14:16:19Z")
Libra wrote: > Libra > R is great! maybe too great for your requirements > rb-gsl is easy for example this will print you a nice gauss-shape graph from rb-gsl-1.8.3/samples/histogram/gauss.rb > sigma, mean, height, = h.fit\_gaussian > > x = GSL::Vector.linspace(-MAX, MAX, 100) > y = height\*Ran::gaussian\_pdf(x-mean, sigma) > GSL::graph(h, [x, y], “-T X -C -g 3”) NICE! cauchy exponential power poisson etc. also available ruby - making maths easy ---
**Author:** ![Libra](https://www.ruby-forum.com/letter_avatar_proxy/v4/letter/l/ed655f/32.png) [@Libra](https://www.ruby-forum.com/u/Libra)\ **Post date:** [April 13, 2007, 2:50am UTC](https://www.ruby-forum.com/t/probability-distributions-library-in-ruby/91872/5 "2007-04-13T02:50:30Z")
On 13 Apr 2007, at 09:35, Alex G. wrote: > > TIA > > > > Libra > > If you are comfortable with R, you can use RSRuby (http:// > web.kuicr.kyoto-u.ac.jp/~alexg/rsruby/) to generate numbers from > any its distribution functions. A quick bit of googling found the missing Bernoulli distribution function: [http://rss.acs.unt.edu/Rdoc/library/Rlab/html/Bernoulli.html](http://rss.acs.unt.edu/Rdoc/library/Rlab/html/Bernoulli.html) It seems to be part of a CRAN package called Rlab: [http://cran.r-project.org/src/contrib/Descriptions/Rlab.html](http://cran.r-project.org/src/contrib/Descriptions/Rlab.html) You should be able to install and then access this library through RSRuby to get your complete set of functions. Alex G. Bioinformatics Center Kyoto University ---
**Author:** ![Libra](https://www.ruby-forum.com/letter_avatar_proxy/v4/letter/l/ed655f/32.png) [@Libra](https://www.ruby-forum.com/u/Libra)\ **Post date:** [August 25, 2007, 6:06am UTC](https://www.ruby-forum.com/t/probability-distributions-library-in-ruby/91872/6 "2007-08-25T06:06:26Z")
Roger P. wrote: > u = rand > > > Libra wrote: > > > > > GSL::graph(h, [x, y], “-T X -C -g 3”) > > > NICE! > > > > cauchy exponential power poisson etc. also available > > ruby - making maths easy There is also RSRuby, a way of calling the R libraries, including their probability distribution routines, from Ruby. I don’t know anything about the ones in GSL, but I know the algorithms in R are first-rate, and I wouldn’t code my own no matter _how_ bored I got. 🙂 ---
**Author:** ![Libra](https://www.ruby-forum.com/letter_avatar_proxy/v4/letter/l/ed655f/32.png) [@Libra](https://www.ruby-forum.com/u/Libra)\ **Post date:** [August 23, 2007, 11:55pm UTC](https://www.ruby-forum.com/t/probability-distributions-library-in-ruby/91872/7 "2007-08-23T23:55:59Z")
From wikipedia : algorithm for generating pseudo poissons: def poisson(lambda) # init l = Math.exp(-lambda) k = 0 p = 1 while p \>= l k += 1 u = rand p = p \*u end return k -1 end only returns ints, but hey, they center around lambda gl. -Roger maw wrote: > Libra wrote: > > > Libra > > R is great! maybe too great for your requirements > > rb-gsl is easy > > for example this will print you a nice gauss-shape graph > from rb-gsl-1.8.3/samples/histogram/gauss.rb > > > sigma, mean, height, = h.fit\_gaussian > > > > x = GSL::Vector.linspace(-MAX, MAX, 100) > > y = height\*Ran::gaussian\_pdf(x-mean, sigma) > > GSL::graph(h, [x, y], “-T X -C -g 3”) > > NICE! > > cauchy exponential power poisson etc. also available > ruby - making maths easy