RANLIB
General Random Number Generators (RNG's)
RANLIB
is a C 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.
Note that this C version of RANLIB was NOT created by simply
running the original FORTRAN77 source code through the f2c program!
If you have ever looked at the resultant source code from such a process,
you know it was never meant for human eyes.
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:
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GENBET, Beta distribution;
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GENCHI, Chi-Square distribution;
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GENEXP, Exponential distribution;
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GENF, F distribution;
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GENGAM, Gamma distribution;
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GENMN, multivariate normal distribution;
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GENMUL, multinomial distribution;
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GENNCH, noncentral Chi-Square distribution;
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GENNF, noncentral F distribution;
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GENNOR, normal distribution;
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GENUNF, uniform distribution on [0,1];
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IGNBIN, binomial distribution;
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IGNLGI, uniform distribution on integers between 1 and 2147483562;
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IGNNBN, negative binomial distribution.
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IGNPOI, Poisson distribution.
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IGNUIN, uniform distribution on integers in a given range.
Licensing:
The computer code and data files 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:
ASA183,
a C library which
implements a random number generator (RNG),
by Wichman and Hill.
This is a C version of Applied Statistics Algorithm 183.
LOG_NORMAL_TRUNCATED_AB,
a C library which
returns quantities associated with the log normal Probability
Distribution Function (PDF) truncated to the interval [A,B].
NORMAL,
a C library which
computes elements of a
sequence of pseudorandom normally distributed values.
RAND48,
a C program which
demonstrates the use of the rand48 family of random number generators
(RNG's) available in the C/C++ standard library.
RANDLC,
a C library which
implements a random number generator (RNG)
used by the NAS Benchmark programs.
RNGLIB,
a C library which
implements a random number generator (RNG) with splitting facilities,
allowing multiple independent streams to be computed,
by L'Ecuyer and Cote.
UNIFORM,
a C library which
computes elements of a pseudorandom uniform sequence.
VAN_DER_CORPUT,
a C library which
computes elements of a 1D van der Corput Quasi Monte Carlo (QMC) sequence
using a simple interface.
WALKER_SAMPLE,
a C library which
efficiently samples a discrete probability vector using
Walker sampling.
Author:
Original FORTRAN77 version by Barry Brown, James Lovato.
C version by John Burkardt.
Reference:
-
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.
-
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.
-
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.
-
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.
-
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.
-
Russell Cheng,
Generating Beta Variates with Nonintegral Shape Parameters,
Communications of the ACM,
Volume 21, Number 4, April 1978, pages 317-322.
-
Luc Devroye,
Non-Uniform Random Variate Generation,
Springer, 1986,
ISBN: 0387963057,
LC: QA274.D48.
-
Voratas Kachitvichyanukul, Bruce Schmeiser,
Binomial Random Variate Generation,
Communications of the ACM,
Volume 31, Number 2, February 1988, page 216-222.
-
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:
Examples and Tests:
List of Routines:
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CH_CAP capitalizes a single character.
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COVAR computes the covariance of two vectors.
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GENBET generates a beta random deviate.
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GENCHI generates a Chi-Square random deviate.
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GENEXP generates an exponential random deviate.
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GENF generates an F random deviate.
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GENGAM generates a Gamma random deviate.
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GENMN generates a multivariate normal deviate.
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GENMUL generates a multinomial random deviate.
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GENNCH generates a noncentral Chi-Square random deviate.
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GENNF generates a noncentral F random deviate.
-
GENNOR generates a normal random deviate.
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GENPRM generates and applies a random permutation to an array.
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GENUNF generates a uniform random deviate.
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I4_MAX returns the maximum of two I4's.
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I4_MIN returns the smaller of two I4's.
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IGNBIN generates a binomial random deviate.
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IGNNBN generates a negative binomial random deviate.
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IGNPOI generates a Poisson random deviate.
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IGNUIN generates a random integer in a given range.
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LENNOB counts the length of a string, ignoring trailing blanks.
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PHRTST converts a phrase to a pair of random number generator seeds.
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PRCOMP prints covariance information.
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R4_MAX returns the maximum of two R4's.
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R4_MIN returns the minimum of two R4's.
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S_EQI reports whether two strings are equal, ignoring case.
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SDOT forms the dot product of two vectors.
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SETCOV sets a covariance matrix from variance and common correlation.
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SETGMN sets data for the generation of multivariate normal deviates.
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SEXPO evaluates the standard exponential distribution.
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SGAMMA returns a deviate from the standard Gamma distribution.
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SNORM returns a deviate from the standard normal distribution.
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SPOFA factors a real symmetric positive definite matrix.
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STATS computes statistics for a given array.
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TRSTAT returns the mean and variance for distributions.
You can go up one level to
the C source codes.
Last revised on 02 April 2013.