# Distributions in R

August 18, 2010
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(This article was first published on Revolutions, and kindly contributed to R-bloggers)

One of the R language’s most powerful features is its ability to deal with random distributions: not just generating random numbers from various distributions (based on a very powerful pseudo-random number generator), but also calculating densities, probabilities, and quintiles. John Cook provides a handy reference chart listing all of the distributions supported by standard R (reproduced below — and there are many other distributions supported by contributed packages), and also explains the elegant naming scheme for the various functions.

 Distribution Base name Parameters beta `beta` `shape1`, `shape2, ncp` binomial `binom` `size`, `prob` Cauchy `cauchy` `location`, `scale` chi-squared `chisq` `df, ncp` exponential `exp` `rate` F `f` `df1`, `df2, ncp` gamma `gamma` `shape`, `rate` geometric `geom` `p` hypergeometric `hyper` `m`, `n`, `k` log-normal `lnorm` `meanlog`, `sdlog` logistic `logis` `location`, `scale` negative binomial `nbinom` `size`, `prob` normal `norm` `mean`, `sd` Poisson `pois` `lambda` Student t `t` `df, ncp` uniform `unif` `min`, `max` Weibull `weibull` `shape`, `scale`

Updated Aug 20: added the ncp parameter to beta, chisq, f, and t with thanks to Doug Bates’ comment below.

John D Cook: Distributions in R and S-PLUS

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