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dc.contributor.advisorHam, Joe S.
dc.creatorScott, Douglas Meloy
dc.description.abstractAn algorithm is presented which combines the techniques of statistical simulation and numerical integration, thus furnishing improved estimates of cumulative distribution functions. The method uses statistical estimation techniques to form a statistic possessing an approximate normal distribution. A post-stratification sample is used to form a control variable correction for the original stratified numerical estimate, and this combination results in a competitor for stratified Monte Carlo sampling. Examples are presented for known statistical distributions and for an actual electronics system. A branch and bound algorithm, which can reduce the amount of computations necessary for both control variable stratified Monte Carlo sampling, is developed for monotone functions.en
dc.format.extent77 leavesen
dc.rightsThis thesis was part of a retrospective digitization project authorized by the Texas A&M University Libraries. Copyright remains vested with the author(s). It is the user's responsibility to secure permission from the copyright holder(s) for re-use of the work beyond the provision of Fair Use.en
dc.subject.classification1974 Dissertation S425
dc.titleDistribution approximation by control variable Monte Carlo samplingen
dc.typeThesisen A&M Universityen of Philosophyen
dc.format.digitalOriginreformatted digitalen
dc.publisher.digitalTexas A&M University. Libraries

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