GNU Octave Manual Version 3 by John W. Eaton, David Bateman, Søren Hauberg Paperback (6"x9"), 568 pages ISBN 095461206X RRP £24.95 ($39.95) 
24.7 Random Number Generation
Octave can generate random numbers from a large number of distributions. The samples are computed from the basic random number generators described in section 16.5 Random Matrices.
The following table summarizes the available random number generators (in alphabetical order).
Distribution  Function

Beta Distribution  betarnd

Binomial Distribution  binornd

Cauchy Distribution  cauchy_rnd

ChiSquare Distribution  chi2rnd

Univariate Discrete Distribution  discrete_rnd

Empirical Distribution  empirical_rnd

Exponential Distribution  exprnd

F Distribution  frnd

Gamma Distribution  gamrnd

Geometric Distribution  geornd

Hypergeometric Distribution  hygernd

Laplace Distribution  laplace_rnd

Logistic Distribution  logistic_rnd

LogNormal Distribution  lognrnd

Pascal Distribution  nbinrnd

Univariate Normal Distribution  normrnd

Poisson Distribution  poissrnd

t (Student) Distribution  trnd

Univariate Discrete Distribution  unidrnd

Uniform Distribution  unifrnd

Weibull Distribution  wblrnd

Wiener Process  wienrnd

 Function File: betarnd (a, b, r, c)
 Function File: betarnd (a, b, sz)
 Return an r by c or
size (sz)
matrix of random samples from the Beta distribution with parameters a and b. Both a and b must be scalar or of size r by c. If r and c are omitted, the size of the result matrix is the common size of a and b.
 Function File: binornd (n, p, r, c)
 Function File: binornd (n, p, sz)
 Return an r by c or a
size (sz)
matrix of random samples from the binomial distribution with parameters n and p. Both n and p must be scalar or of size r by c. If r and c are omitted, the size of the result matrix is the common size of n and p.
 Function File: cauchy_rnd (lambda, sigma, r, c)
 Function File: cauchy_rnd (lambda, sigma, sz)
 Return an r by c or a
size (sz)
matrix of random samples from the Cauchy distribution with parameters lambda and sigma which must both be scalar or of size r by c. If r and c are omitted, the size of the result matrix is the common size of lambda and sigma.
 Function File: chi2rnd (n, r, c)
 Function File: chi2rnd (n, sz)
 Return an r by c or a
size (sz)
matrix of random samples from the chisquare distribution with n degrees of freedom. n must be a scalar or of size r by c. If r and c are omitted, the size of the result matrix is the size of n.
 Function File: discrete_rnd (n, v, p)
 Function File: discrete_rnd (v, p, r, c)
 Function File: discrete_rnd (v, p, sz)
 Generate a row vector containing a random sample of size n from the univariate distribution which assumes the values in v with probabilities p. n must be a scalar. If r and c are given create a matrix with r rows and c columns. Or if sz is a vector, create a matrix of size sz.
 Function File: empirical_rnd (n, data)
 Function File: empirical_rnd (data, r, c)
 Function File: empirical_rnd (data, sz)
 Generate a bootstrap sample of size n from the empirical distribution obtained from the univariate sample data. If r and c are given create a matrix with r rows and c columns. Or if sz is a vector, create a matrix of size sz.
 Function File: exprnd (lambda, r, c)
 Function File: exprnd (lambda, sz)
 Return an r by c matrix of random samples from the exponential distribution with mean lambda, which must be a scalar or of size r by c. Or if sz is a vector, create a matrix of size sz. If r and c are omitted, the size of the result matrix is the size of lambda.
 Function File: frnd (m, n, r, c)
 Function File: frnd (m, n, sz)
 Return an r by c matrix of random samples from the F distribution with m and n degrees of freedom. Both m and n must be scalar or of size r by c. If sz is a vector the random samples are in a matrix of size sz. If r and c are omitted, the size of the result matrix is the common size of m and n.
 Function File: gamrnd (a, b, r, c)
 Function File: gamrnd (a, b, sz)
 Return an r by c or a
size (sz)
matrix of random samples from the Gamma distribution with parameters a and b. Both a and b must be scalar or of size r by c. If r and c are omitted, the size of the result matrix is the common size of a and b.See also gamma, gammaln, gammainc, gampdf, gamcdf, gaminv
 Function File: geornd (p, r, c)
 Function File: geornd (p, sz)
 Return an r by c matrix of random samples from the geometric distribution with parameter p, which must be a scalar or of size r by c. If r and c are given create a matrix with r rows and c columns. Or if sz is a vector, create a matrix of size sz.
 Function File: hygernd (t, m, n, r, c)
 Function File: hygernd (t, m, n, sz)
 Function File: hygernd (t, m, n)
 Return an r by c matrix of random samples from the hypergeometric distribution with parameters t, m, and n. The parameters t, m, and n must positive integers with m and n not greater than t. The parameter sz must be scalar or a vector of matrix dimensions. If sz is scalar, then a sz by sz matrix of random samples is generated.
 Function File: laplace_rnd (r, c)
 Function File: laplace_rnd (sz);
 Return an r by c matrix of random numbers from the Laplace distribution. Or if sz is a vector, create a matrix of sz.
 Function File: logistic_rnd (r, c)
 Function File: logistic_rnd (sz)
 Return an r by c matrix of random numbers from the logistic distribution. Or if sz is a vector, create a matrix of sz.
 Function File: lognrnd (mu, sigma, r, c)
 Function File: lognrnd (mu, sigma, sz)
 Return an r by c matrix of random samples from the lognormal distribution with parameters mu and sigma. Both mu and sigma must be scalar or of size r by c. Or if sz is a vector, create a matrix of size sz. If r and c are omitted, the size of the result matrix is the common size of mu and sigma.
 Function File: nbinrnd (n, p, r, c)
 Function File: nbinrnd (n, p, sz)
 Return an r by c matrix of random samples from the Pascal (negative binomial) distribution with parameters n and p. Both n and p must be scalar or of size r by c. If r and c are omitted, the size of the result matrix is the common size of n and p. Or if sz is a vector, create a matrix of size sz.
 Function File: normrnd (m, s, r, c)
 Function File: normrnd (m, s, sz)
 Return an r by c or
size (sz)
matrix of random samples from the normal distribution with parameters mean m and standard deviation s. Both m and s must be scalar or of size r by c. If r and c are omitted, the size of the result matrix is the common size of m and s.
 Function File: poissrnd (lambda, r, c)
 Return an r by c matrix of random samples from the Poisson distribution with parameter lambda, which must be a scalar or of size r by c. If r and c are omitted, the size of the result matrix is the size of lambda.
 Function File: trnd (n, r, c)
 Function File: trnd (n, sz)
 Return an r by c matrix of random samples from the t (Student) distribution with n degrees of freedom. n must be a scalar or of size r by c. Or if sz is a vector create a matrix of size sz. If r and c are omitted, the size of the result matrix is the size of n.
 Function File: unidrnd (mx);
 Function File: unidrnd (mx, v);
 Function File: unidrnd (mx, m, n, ...);
 Return random values from discrete uniform distribution, with maximum value(s) given by the integer mx, which may be a scalar or multidimensional array. If mx is a scalar, the size of the result is specified by the vector v, or by the optional arguments m, n, .... Otherwise, the size of the result is the same as the size of mx.
 Function File: unifrnd (a, b, r, c)
 Function File: unifrnd (a, b, sz)
 Return an r by c or a
size (sz)
matrix of random samples from the uniform distribution on [a, b]. Both a and b must be scalar or of size r by c. If r and c are omitted, the size of the result matrix is the common size of a and b.
 Function File: wblrnd (scale, shape, r, c)
 Function File: wblrnd (scale, shape, sz)
 Return an r by c matrix of random samples from the Weibull distribution with parameters scale and shape which must be scalar or of size r by c. Or if sz is a vector return a matrix of size sz. If r and c are omitted, the size of the result matrix is the common size of alpha and sigma.
 Function File: wienrnd (t, d, n)
 Return a simulated realization of the ddimensional Wiener Process on the interval [0, t]. If d is omitted, d = 1 is used. The first column of the return matrix contains time, the remaining columns contain the Wiener process. The optional parameter n gives the number of summands used for simulating the process over an interval of length 1. If n is omitted, n = 1000 is used.
ISBN 095461206X  GNU Octave Manual Version 3  See the print edition 