RANLIB
General Random Number Generators (RNG's)

RANLIB is a FORTRAN77 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.

RANLIB relies on streams of uniform random numbers generated by a lower level package called RNGLIB. A copy of RNGLIB must be available in order for RANLIB to executed. The RNGLIB routines provide 32 virtual random number generators. Each generator can provide 1,048,576 blocks of numbers, and each block is of length 1,073,741,824. Any generator can be set to the beginning or end of the current block or to its starting value. Packaging is provided so that if these capabilities are not needed, a single generator with period 2.3 X 10^18 is seen.

The routines, and the probability density functions they sample, include:

• GENBET, Beta distribution;
• GENCHI, Chi-Square distribution;
• GENEXP, Exponential distribution;
• GENF, F distribution;
• GENGAM, Gamma distribution;
• GENMN, multivariate normal distribution;
• GENMUL, multinomial distribution;
• GENNCH, noncentral Chi-Square distribution;
• GENNF, noncentral F distribution;
• GENNOR, normal distribution;
• GENUNF, uniform distribution on [0,1];
• IGNBIN, binomial distribution;
• IGNLGI, uniform distribution on integers between 1 and 2147483562;
• IGNNBN, negative binomial distribution.
• IGNPOI, Poisson distribution.
• IGNUIN, uniform distribution on integers in a given range.

Licensing:

The computer code and data files described and made available on this web page are distributed under the GNU LGPL license.

Languages:

RANLIB is available in a C version and a C++ version and a FORTRAN90 version and a MATLAB version and a Python version.

Related Data and Programs:

FAURE, a FORTRAN90 library which computes elements of a Faure quasirandom sequence.

HALTON, a FORTRAN90 library which computes elements of a Halton quasirandom sequence.

HAMMERSLEY, a FORTRAN90 library which computes elements of a Hammersley quasirandom sequence.

NIEDERREITER2, a FORTRAN90 library which computes elements of a Niederreiter quasirandom sequence with base 2.

NORMAL, a FORTRAN77 library which computes elements of a sequence of pseudorandom normally distributed values.

PDFLIB, a FORTRAN77 library which evaluates Probability Density Functions (PDF's) and produces random samples from them, including beta, binomial, chi, exponential, gamma, inverse chi, inverse gamma, multinomial, normal, scaled inverse chi, and uniform.

RNGLIB, a FORTRAN77 library which implements a random number generator (RNG) with splitting facilities, allowing multiple independent streams to be computed, by L'Ecuyer and Cote.

SOBOL, a FORTRAN90 library which computes elements of a Sobol quasirandom sequence.

UNIFORM, a FORTRAN77 library which computes elements of a pseudorandom uniform sequence.

VAN_DER_CORPUT, a FORTRAN90 library which computes elements of a van der Corput quasirandom sequence.

Author:

Original FORTRAN77 version by Barry Brown, James Lovato. This FORTRAN77 version by John Burkardt.

Reference:

1. Joachim Ahrens, Ulrich Dieter,
   Computer Methods for Sampling From the Exponential and Normal Distributions,
   Communications of the ACM,
   Volume 15, Number 10, October 1972, pages 873-882.
2. Joachim Ahrens, Ulrich Dieter,
   Generating Gamma Variates by a Modified Rejection Technique,
   Communications of the ACM,
   Volume 25, Number 1, January 1982, pages 47-54.
3. Joachim Ahrens, Ulrich Dieter,
   Computer Generation of Poisson Deviates From Modified Normal Distributions,
   ACM Transactions on Mathematical Software,
   Volume 8, Number 2, June 1982, pages 163-179.
4. Joachim Ahrens, Ulrich Dieter,
   Computer Methods for Sampling from Gamma, Beta, Poisson and Binomial Distributions,
   Computing,
   Volume 12, Number 3, September 1974, pages 223-246.
5. Joachim Ahrens, Ulrich Dieter,
   Extensions of Forsythe's Method for Random Sampling from the Normal Distribution,
   Mathematics of Computation,
   Volume 27, Number 124, October 1973, page 927-937.
6. Russell Cheng,
   Generating Beta Variates with Nonintegral Shape Parameters,
   Communications of the ACM,
   Volume 21, Number 4, April 1978, pages 317-322.
7. Luc Devroye,
   Non-Uniform Random Variate Generation,
   Springer, 1986,
   ISBN: 0387963057,
   LC: QA274.D48.
8. Voratas Kachitvichyanukul, Bruce Schmeiser,
   Binomial Random Variate Generation,
   Communications of the ACM,
   Volume 31, Number 2, February 1988, page 216-222.
9. Pierre LEcuyer, Serge Cote,
   Implementing a Random Number Package with Splitting Facilities,
   ACM Transactions on Mathematical Software,
   Volume 17, Number 1, March 1991, pages 98-111.

Source Code:

• ranlib.f, the source code.
• ranlib.sh, commands to compile the source code.

Examples and Tests:

• ranlib_prb.f, a sample calling program.
• ranlib_prb.sh, commands to compile and run the sample program.
• ranlib_prb_output.txt, the output from a run of the sample program.

List of Routines:

• COVAR computes the covariance of two vectors.
• GENBET generates a beta random deviate.
• GENCHI generates a Chi-Square random deviate.
• GENEXP generates an exponential random deviate.
• GENF generates an F random deviate.
• GENGAM generates a Gamma random deviate.
• GENMN generates a multivariate normal deviate.
• GENMUL generates a multinomial random deviate.
• GENNCH generates a noncentral Chi-Square random deviate.
• GENNF generates a noncentral F random deviate.
• GENNOR generates a normal random deviate.
• GENPRM generates and applies a random permutation to an array.
• GENUNF generates a uniform random deviate.
• IGNBIN generates a binomial random deviate.
• IGNNBN generates a negative binomial random deviate.
• IGNPOI generates a Poisson random deviate.
• IGNUIN generates a random integer in a given range.
• LENNOB counts the length of a string, ignoring trailing blanks.
• PHRTST converts a phrase to a pair of random number generator seeds.
• PRCOMP prints covariance information.
• SDOT forms the dot product of two vectors.
• SETCOV sets a covariance matrix from variance and common correlation.
• SETGMN sets data for the generation of multivariate normal deviates.
• SEXPO evaluates the standard exponential distribution.
• SGAMMA returns a deviate from the standard Gamma distribution.
• SNORM returns a deviate from the standard normal distribution.
• SPOFA factors a real symmetric positive definite matrix.
• STATS computes statistics for a given array.
• TRSTAT returns the mean and variance for distributions.

You can go up one level to the FORTRAN77 source codes.