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The exact approximation method in distribution simulation.

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dc.contributor.author Keighley, John David
dc.date.accessioned 2012-07-12T20:44:28Z
dc.date.available 2012-07-12T20:44:28Z
dc.date.created 1989 en_US
dc.date.issued 2012-07-12
dc.identifier.uri http://hdl.handle.net/123456789/1876
dc.description 73 leaves en_US
dc.description.abstract An algorithm for generating random variates quickly, called the exact approximation method is the subject of this thesis. Two other algorithms, the acceptance rejection method, and the inversion method for generating random variates are also included. The exact approximation method uses the acceptance rejection method. The inversion method is a special case of the exact approximation method. To generate random variates quickly using the exact approximation method a function which is a close approximation to the inverse cumulative probability function must be found. The choice of this function is a compromise between it's ease of computation and it's closeness to the inverse cumulative distribution function. Since both factors affect the efficiency of the exact approximation algorithm. en_US
dc.language.iso en_US en_US
dc.subject Random variables. en_US
dc.subject Distribution (Probability theory)-Computer simulation. en_US
dc.title The exact approximation method in distribution simulation. en_US
dc.type Thesis en_US
dc.college las en_US
dc.advisor Larry Scott en_US
dc.department mathematics, computer science, and economics en_US

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