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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
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Showing 31 to 40 of 11507 (0.112 seconds)| 31 |
Changepoint procedure for repeated measures /Juang, Shing-her January 1986 (has links)
No description available.
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On estimation of a cumulative distribution function /Phadia, Eswarlal G. January 1971 (has links)
No description available.
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On characterization of some probability distributions and estimation of the parameters of the Pareto distribution /Wang, Yao Hung January 1971 (has links)
No description available.
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A Kolmogorov-type statistic based on a variation of the bivariate distribution function.Davis, John Howard January 1972 (has links)
No description available.
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Distribution-free tests for ordered alternatives in block designs /Skillings, John H. January 1975 (has links)
No description available.
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Retrodistribution in Brauereien unter besonderer Berücksichtigung des LeergutkreislaufsBebber, Marco January 2010 (has links)
Zugl.: Diplomarbeit
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Lagerausgleichsdistribution : Konzeption eines Verfahrens zur Verbesserung des Servicegrads in Distributionssystemen /Schweiger, Alfred. January 1900 (has links)
Diss.--München--Universität der Bundeswehr, 1989. / Bibliogr. p. [401]-414.
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A type of 'inverseness' of certain distributions and the inverse normal distributionTlakula, Stanley Nkhensani January 1978 (has links)
Thesis (M. Sc. (Mathematical Statistics)) -- University of the North, 1978 / Refer to the document
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Characterizations of Distributions by Conditional ExpectationChang, Tao-Wen 19 June 2001 (has links)
In this thesis, first we replace the condition X ¡Ø y in Huang and Su (2000) by X ¡Ù y and give necessary and sufficient conditions such that there exists a random variable X satisfying that E(g(X)| X ¡Ø y)=h(y) f(y )/ F(y), " y Î CX, where CX is the support of X.Next, we investigate necessary and sufficient conditions such that h(y)=E(g(X) | X ¡Ø y ), for a given function h and extend these results to bivariate case.
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Comparison of estimators for the parameters of the poisson-gamma marginal distributionKerr, Barbara Sue January 2010 (has links)
Typescript (photocopy). / Digitized by Kansas Correctional Industries
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