Home > C,C++ > Random numbers

Random numbers

Related Categories

C++ Random Number Library  
This is a C++ library for generating sequences of random numbers from a wide variety of distributions. It is particularly appropriate for the situation where one requires sequences of identically distributed random numbers since the set up time for each type of distribution is relatively long but it is efficient when generating each new random number. The library includes classes for generating random numbers from a number of distributions and is easily extended to be able to generate random numbers from almost any of the standard distributions.
Submitted: Jan 09, 2000
Random Numbers in Matlab, C and Java  
None of these languages provide facilities for choosing truly random numbers. They just provide pseudo-random numbers. But, we'll pretend that they are random for now, and address the details later.
Submitted: Mar 09, 2005
Pseudo Random Number Generators  
This page contains C++ code libraries for some very good random number generators. The basic random number generators make floating point or integer random numbers with uniform distributions. The non-uniform random number generators make random variates with the following distributions: normal, bernoulli, poisson, binomial, hypergeometric, noncentral hypergeometric, extended hypergeometric, multinomial, multivariate hypergeometric, multivariate noncentral hypergeometric, multivariate extended hypergeometric, and shuffling.
Submitted: Nov 12, 2002
Mersenne Twister: A random number generator  
Mersenne Twister(MT) is a pseudorandom number generator developped by Makoto Matsumoto and Takuji Nishimura (alphabetical order) during 1996-1997. MT has the following merits: It is designed with consideration on the flaws of various existing generators. The algorithm is coded into a C source downloadable below. Far longer period and far higher order of equidistribution than any other implemented generators (it is proved that the period is 2^19937-1, and 623-dimensional equidistribution property is assured). Fast generation (although it depends on the system, it is reported that MT is sometimes faster than the standard ANSI-C library in a system with pipeline and cache memory). Efficient use of the memory (the implemented C-code mt19937.c consumes only 624 words of working area).
Submitted: Jun 20, 1999
Random number generators  
This server is maintained by a team of mathematicians and computer scientists led by Peter Hellekalek at the University of Salzburg's Mathematics Department. We present results and links on this fundamental topic in stochastic simulation, some of them due to our own research in this field. Enjoy the data and allow for necessary incompleteness and subjectivity (an unmoderated but richer collection of network-resouces on random number generators is located on this server as part of the WWW Virtual Library).
Submitted: Aug 31, 1998
Newran  
This C++ library is intended for generating streams of random numbers from a variety of distributions. The aim is to provide reasonably efficient methods for generating random numbers from the standard distributions, and also to provide an easy way for users to build generators for other continuous and discrete distributions.
Submitted: Dec 20, 1999
one-over-f (1/f) noise  
1/f noise ("one-over-f noise", occasionally called "flicker noise" or "pink noise") is a type of noise whose power spectra P(f) as a function of the frequency f behaves like: P(f) = 1/f^a, where the exponent a is very close to 1 (that's where the name "1/f noise" comes from). The page lists and classifies links to publications regarding 1/f noise.
Submitted: Jul 07, 1999
random  
Random numbers library at NETLIB.
Submitted: Aug 31, 1998
RNG Implementations  
Implementations of linear and inversive generators are available in ANSI-C. RNGs are deterministic algorithms that produce numbers with certain distribution properties. Roughly speaking, these numbers should behave similar to realizations of independent, identically distributed random variables. Every RNG has its deficiencies. No RNG is appropriate for all tasks. In order to verify our simulation results, we should be able to choose from a whole arsenal of widely different RNGs.
Submitted: Jul 04, 1999
Linear combination of chi-squared random variables  
X1,...,Xn are independent (non-central) chi-squared random variables and Z is a normal random variable independent of X1,...,Xn. This program calculates the probability Pr(a1* X1 + ... + an *Xn + a0*Z < x). The source code includes a main function.
Submitted: Nov 14, 1999
RanLip - universal nonuniform multivariate random variate generator  
RanLip is a method of generation of random variates with arbitrary Lipschitz-continuous densities, which works in the univariate and multivariate cases, in up to 5-6 variables. Implemented in C++.
Submitted: Nov 21, 2006



  Privacy - Trademarks - Feedback - Terms of Use Copyright The MathWorks, Inc.