JSM 2005 - Toronto

Abstract #304122

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 136
Type: Contributed
Date/Time: Monday, August 8, 2005 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #304122
Title: Mixture Models, SEMOR, and BARS
Author(s): Mark Lancaster*+ and Kert Viele
Companies: University of Kentucky and University of Kentucky
Address: 3693 Arbor Drive, Lexington, 40517, United States
Keywords: Mixtures ; SEMOR ; BARS ; Neuroscience
Abstract:

A nerve from a crayfish is repeatedly stimulated, and from this stimulation a random pattern of nerve "firings" and "nonfirings" emerges. In the process of classifying these nerve patterns and estimating the underlying firing function, we explore data-specific issues involved with the implementation of the EM algorithm, self-modeling regression (SEMOR), and Bayesian adaptive regression splines (BARS).


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Revised March 2005