Using geometry to select one dimensional exponential families that are monotone likelihood ratio in the sample space, are weakly unimodal and can be parametrized by a measure of central tendency

ECU Author/Contributor (non-ECU co-authors, if there are any, appear on document)
Paul,Anaya-Izquierdo,Karim Vos (Creator)
Institution
East Carolina University (ECU )
Web Site: http://www.ecu.edu/lib/

Abstract: One dimensional exponential families on finite sample spaces are studied using the geometry of the simplex Δn°-1 and that of a transformation Vn-1 of its interior. This transformation is the natural parameter space associated with the family of multinomial distributions. The space Vn-1 is partitioned into cones that are used to find one dimensional families with desirable properties for modeling and inference. These properties include the availability of uniformly most powerful tests and estimators that exhibit optimal properties in terms of variability and unbiasedness.

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Publication
Other
Language: English
Date: 2014

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Using geometry to select one dimensional exponential families that are monotone likelihood ratio in the sample space, are weakly unimodal and can be parametrized by a measure of central tendencyhttp://hdl.handle.net/10342/8311The described resource references, cites, or otherwise points to the related resource.