JSM 2005 - Toronto

Abstract #302430

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 242
Type: Invited
Date/Time: Tuesday, August 9, 2005 : 10:30 AM to 12:20 PM
Sponsor: IMS
Abstract - #302430
Title: Local Likelihood and Mixture Modeling
Author(s): Catherine Loader*+ and Ramani S. Pilla
Companies: Case Western Reserve University and Case Western Reserve University
Address: Department of Statistics, Beachwood, OH, 44122,
Keywords:
Abstract:

Local likelihood was introduced by Tibshirani and Hastie (1987) as a method of smoothing data when the responses do not follow a Gaussian distribution. Extensive theoretical and methodological advances have been made since then, but largely for cases where there is a single function, such as the conditional mean, to estimate. In this talk, the local likelihood method will be extended to responses from a mixture model. This will lead to many new challenges and much additional flexibility as locations, mixing weights, and the number of components are allowed to vary spatially throughout the predictor space. A result of this work is a comprehensive solution to the overdispersion problem.

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Revised March 2005