Abstract: Random variate generation is a fundamental aspect of simulation modeling and analysis. The objective of random variate generation is to produce observations that have the stochastic properties of a given random variable. To this end, methods and algorithms have been developed to generate random variates that are accurate (representative of the target distribution) and computationally efficient. This paper presents a history of random variate generation including distribution sampling methods used prior to the introduction of digital computers, as well as the evolution of random variate generators for continuous and discrete distributions and stochastic point processes.
Publication Year: 2017
Publication Date: 2017-12-01
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 2
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