Many methods for generating variates from discrete distributions have been developed over the past years. They vary from simple to complicated, from specific to general. Some are based on interesting underlying theory, while others are more concerned with efficient computer implementation. / This dissertation is directed toward the latter. We describe methods that are best suited for efficient (fast) computer implementation. We develop specific programs for both the Poisson and the binomial distributions with two versions of each, one for when the parameters are fixed and the other for when the parameters change from call to call. These programs are developed with a spare-no-expense attitude, and timing comparisons will support our belief that they are faster than any other published methods. / For the fixed-parameter case, an algorithm which combines the table look-up, the square histogram (Marsaglia's lecture notes), and the direct search method is given. We will apply the algorithm to the Poisson and the binomial distributions. / For the variable-parameter Poisson case, we take advantage of Marsaglia's (1986) approach and incorporate additional techniques in order to have a Poisson variate generator which works for any value of $\lambda$, using, most of the time, the integer part of a polynomial in a normal variate. We extend the procedure to the binomial distribution. / Source: Dissertation Abstracts International, Volume: 54-07, Section: B, page: 3697. / Major Professor: George Marsaglia. / Thesis (Ph.D.)--The Florida State University, 1993.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_76985 |
| Contributors | Lee, Wen-Chiung., Florida State University |
| Source Sets | Florida State University |
| Language | English |
| Detected Language | English |
| Type | Text |
| Format | 111 p. |
| Rights | On campus use only. |
| Relation | Dissertation Abstracts International |
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