JSM 2004 - Toronto

Abstract #300489

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Activity Number: 317
Type: Invited
Date/Time: Wednesday, August 11, 2004 : 10:30 AM to 12:20 PM
Sponsor: Noether Award Committee
Abstract - #300489
Title: Nonparametrics and Mixture Models
Author(s): Tom Hettmansperger*+
Companies: Pennsylvania State University
Address: 317 Thomas Bldg., University Park, PA, 16802,
Keywords: nonparametric statistics ; semiparametric models ; EM algorithm ; nontransitive samples ; Efron dice
Abstract:

In recent years mixture models have provided a very flexible approach to modeling diverse phenomena. EM algorithms have provided a convenient approach to computation so that mixtures can be fitted to data. We will discuss some work on semiparametric mixtures in which the underlying component distributions are not specified by any parametric model. In particular, we do not wish to impose the condition that the components come from the same family. We will discuss situations in which the mixing proportions and the underlying component distribution functions can be estimated along with the number of components in the mixture. When comparing three samples, if the samples arise from certain mixture distributions, nontransitivities can arise. We will discuss the structure of such mixtures and propose nonparametric tests to detect the nontransitivities. All proposed methods will be illustrated on datasets.

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Revised March 2004