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Saddlepoint approximations to distribution functions

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dc.contributor.author Hauschildt, Reimar
dc.date.accessioned 2011-06-07T19:18:52Z
dc.date.available 2011-06-07T19:18:52Z
dc.date.copyright 1969
dc.date.issued 2011-06-07T19:18:52Z
dc.identifier.uri http://hdl.handle.net/2429/35169
dc.description.abstract In this thesis we present two approximations to the distribution function of the sum of n independent random variables. They are obtained from generalizations of asymptotic expansions derived by Rubin and Zidek who considered the case of chi random variables. These expansions are obtained from Gurland's inversion formula for the distribution function by using an adaptation of Laplace's method for integrals. By means of numerical results obtained for a variety of common distributions and small values of n these approximations arc compared to the classical methods of Edgeworth and Cramer. Finally, the method is used to obtain approximations to the non-central chi-square distribution and to the doubly non-central F-distribution for various cases defined in terms of its parameters. en
dc.language.iso eng en
dc.publisher University of British Columbia en
dc.relation.ispartof Retrospective Theses and Dissertations, 1919-2007 en
dc.relation.ispartofseries UBC Retrospective Theses Digitization Project [http://www.library.ubc.ca/archives/retro_theses/] en
dc.subject Distribution (Probability theory) en
dc.title Saddlepoint approximations to distribution functions en
dc.type Text en
dc.degree.name Master of Science - MSc en
dc.degree.discipline Mathematics en
dc.degree.grantor University of British Columbia en
dc.type.text Thesis/Dissertation en
dc.description.affiliation Science, Faculty of en
dc.degree.campus UBCV en
dc.description.scholarlevel Graduate en

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