A sufficient normality condition for Turing's formula -

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dc.contributor.authorEl Bayeh, Frederic Michael
dc.contributor.departmentDepartment of Mathematics
dc.contributor.facultyFaculty of Arts and Sciences
dc.contributor.institutionAmerican University of Beirut
dc.date2017
dc.date.accessioned2017-12-11T16:30:49Z
dc.date.available2017-12-11T16:30:49Z
dc.date.issued2017
dc.date.submitted2017
dc.descriptionThesis. M.S. American University of Beirut. Department of Mathematics, 2017. T:6603
dc.descriptionAdvisor : Dr. Abbas Al Hakim, Associate Professor, Mathematics ; Committee members : Dr. Nabil Nassif, Professor, Mathematics ; Dr. Stefano Monni, Assistant Professor, Mathematics.
dc.descriptionIncludes bibliographical references (leaves 53-54)
dc.description.abstractIn this thesis, we will study the Turing's formula, which is a formula used to estimate the sample coverage probability. We will establish a necessary and sufficient condition for the asymptotic normality (i.e. a central limit theorem for Turing's formula). Also, we will discuss its statistical applications.
dc.format.extent1 online resource ( ix, 54 leaves)
dc.identifier.otherb19185996
dc.identifier.urihttp://hdl.handle.net/10938/20973
dc.language.isoen
dc.relation.ispartofTheses, Dissertations, and Projects
dc.subject.classificationT:006603
dc.subject.lcshLimit theorems (Probability theory)
dc.subject.lcshProbabilities.
dc.subject.lcshEstimation theory.
dc.titleA sufficient normality condition for Turing's formula -
dc.typeThesis

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