NORMAL, a MATLAB library which computes normally distributed pseudorandom numbers.
NORMAL is based on two simple ideas:
Using these ideas, it is not too hard to generate normal sequences of real or complex values, of single or double precision. These values can be generated as single quantities, vectors or matrices. An associated seed actually determines the sequence. Varying the seed will result in producing a different sequence.
The fundamental underlying random number generator used here is based on a simple, old, and limited linear congruential random number generator originally used in the IBM System 360.
This library makes it possible to compare certain computations that use normal random numbers, written in C, C++, FORTRAN77, FORTRAN90, MATLAB or Python.
The computer code and data files described and made available on this web page are distributed under the GNU LGPL license.
NORMAL is available in a C version and a C++ version and a FORTRAN90 version and a MATLAB version and a Python version.
MATLAB_RANDOM, MATLAB programs which illustrate the use of Matlab's random number generators.
RANDOM_SORTED, a MATLAB library which generates vectors of random values which are already sorted.
RANLIB, a MATLAB library which produces random samples from Probability Density Functions (PDF's), including Beta, Chi-square Exponential, F, Gamma, Multivariate normal, Noncentral chi-square, Noncentral F, Univariate normal, random permutations, Real uniform, Binomial, Negative Binomial, Multinomial, Poisson and Integer uniform, by Barry Brown and James Lovato.
RNGLIB, a MATLAB library which implements a random number generator (RNG) with splitting facilities, allowing multiple independent streams to be computed, by L'Ecuyer and Cote.
TRUNCATED_NORMAL, a MATLAB library which works with the truncated normal distribution over [A,B], or [A,+oo) or (-oo,B], returning the probability density function (PDF), the cumulative density function (CDF), the inverse CDF, the mean, the variance, and sample values.
UNIFORM, a MATLAB library which computes a sequence of uniformly distributed pseudorandom values.