The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
Computer Generation of Random Variables Using the Ratio of Uniform Deviates
ACM Transactions on Mathematical Software (TOMS)
Computer Generation of Poisson Deviates from Modified Normal Distributions
ACM Transactions on Mathematical Software (TOMS)
Generating gamma variates by a modified rejection technique
Communications of the ACM
Computer methods for sampling from the exponential and normal distributions
Communications of the ACM
A fast procedure for generating normal random variables
Communications of the ACM
Algorithm 780: exponential pseudorandom distribution
ACM Transactions on Mathematical Software (TOMS)
Gaussian random number generators
ACM Computing Surveys (CSUR)
Gaussian variable neighborhood search for continuous optimization
Computers and Operations Research
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Three algorithms for sampling from exponential, Cauchy and normal distributions are developed. They are based on the "exact approximation" method, and their expected numbers of consumed uniform deviates are less than 1.04 per sample from the target distributions. The algorithms are simple and easily implemented in any desired precision. They require no space for long tables of auxiliary vectors, merely a few constants are needed. Nevertheless, their speed compares well with the performance of much more complex and table-aided sampling procedures.