% -*- texinfo -*-
% @deftypefn {Function File} @var{r} = random(@var{name}, @var{arg1})
% @deftypefnx{Function File} @var{r} = random(@var{name}, @var{arg1}, @var{arg2})
% @deftypefnx{Function File} @var{r} = random(@var{name}, @var{arg1}, @var{arg2}, @var{arg3})
% @deftypefnx{Function File} @var{r} = random(@var{name}, ..., @var{s1}, ...)
% Generates pseudo-random numbers from a given one-, two-, or three-parameter
% distribution.
%
% The variable @var{name} must be a string that names the distribution from
% which to sample. If this distribution is a one-parameter distribution @var{arg1}
% should be supplied, if it is a two-paramter distribution @var{arg2} must also
% be supplied, and if it is a three-parameter distribution @var{arg3} must also
% be present. Any arguments following the distribution paramters will determine
% the size of the result.
%
% As an example, the following code generates a 10 by 20 matrix containing
% random numbers from a normal distribution with mean 5 and standard deviation
% 2.
% @example
% R = random('normal', 5, 2, [10, 20]);
% @end example
%
% The variable @var{name} can be one of the following strings
%
% @table @asis
% @item 'beta'
% @itemx 'beta distribution'
% Samples are drawn from the Beta distribution.
% @item 'bino'
% @itemx 'binomial'
% @itemx 'binomial distribution'
% Samples are drawn from the Binomial distribution.
% @item 'chi2'
% @itemx 'chi-square'
% @itemx 'chi-square distribution'
% Samples are drawn from the Chi-Square distribution.
% @item 'exp'
% @itemx 'exponential'
% @itemx 'exponential distribution'
% Samples are drawn from the Exponential distribution.
% @item 'f'
% @itemx 'f distribution'
% Samples are drawn from the F distribution.
% @item 'gam'
% @itemx 'gamma'
% @itemx 'gamma distribution'
% Samples are drawn from the Gamma distribution.
% @item 'geo'
% @itemx 'geometric'
% @itemx 'geometric distribution'
% Samples are drawn from the Geometric distribution.
% @item 'hyge'
% @itemx 'hypergeometric'
% @itemx 'hypergeometric distribution'
% Samples are drawn from the Hypergeometric distribution.
% @item 'logn'
% @itemx 'lognormal'
% @itemx 'lognormal distribution'
% Samples are drawn from the Log-Normal distribution.
% @item 'nbin'
% @itemx 'negative binomial'
% @itemx 'negative binomial distribution'
% Samples are drawn from the Negative Binomial distribution.
% @item 'norm'
% @itemx 'normal'
% @itemx 'normal distribution'
% Samples are drawn from the Normal distribution.
% @item 'poiss'
% @itemx 'poisson'
% @itemx 'poisson distribution'
% Samples are drawn from the Poisson distribution.
% @item 'rayl'
% @itemx 'rayleigh'
% @itemx 'rayleigh distribution'
% Samples are drawn from the Rayleigh distribution.
% @item 't'
% @itemx 't distribution'
% Samples are drawn from the T distribution.
% @item 'unif'
% @itemx 'uniform'
% @itemx 'uniform distribution'
% Samples are drawn from the Uniform distribution.
% @item 'unid'
% @itemx 'discrete uniform'
% @itemx 'discrete uniform distribution'
% Samples are drawn from the Uniform Discrete distribution.
% @item 'wbl'
% @itemx 'weibull'
% @itemx 'weibull distribution'
% Samples are drawn from the Weibull distribution.
% @end table
% @seealso{rand, betarnd, binornd, chi2rnd, exprnd, frnd, gamrnd, geornd, hygernd,
% lognrnd, nbinrnd, normrnd, poissrnd, raylrnd, trnd, unifrnd, unidrnd, wblrnd}
% @end deftypefn