An exhaustive analysis of multiplicative congruential random number generators with modulus 231-1
SIAM Journal on Scientific and Statistical Computing
Mathematical aspects of various methods for sampling from classical distributions
WSC '89 Proceedings of the 21st conference on Winter simulation
Ratio of uniforms as a convenient method for sampling from classical discrete distributions
WSC '89 Proceedings of the 21st conference on Winter simulation
A note on the quality of random variates generated by the ratio of uniforms method
ACM Transactions on Modeling and Computer Simulation (TOMACS)
A rejection technique for sampling from T-concave distributions
ACM Transactions on Mathematical Software (TOMS)
Rejection-inversion to generate variates from monotone discrete distributions
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Automatic sampling with the ratio-of-uniforms method
ACM Transactions on Mathematical Software (TOMS)
Computer Generation of Random Variables Using the Ratio of Uniform Deviates
ACM Transactions on Mathematical Software (TOMS)
A note on transformed density rejection
Computing
Short universal generators via generalized ratio-of-uniforms method
Mathematics of Computation
Random variate generation for exponentially and polynomially tilted stable distributions
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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We use inequalities to design short universal algorithms that can be used to generate random variates from large classes of univariate continuous or discrete distributions (including all log-concave distributions). The expected time is uniformly bounded over all these distributions. The algorithms can be implemented in a few lines of high-level language code. In opposition to other black-box algorithms hardly any setup step is required, and thus it is superior in the changing-parameter case.