Abstract #302158

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JSM 2003 Abstract #302158
Activity Number: 78
Type: Topic Contributed
Date/Time: Monday, August 4, 2003 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Stat. Sciences
Abstract - #302158
Title: Shape Classification Procedures with Applications
Author(s): Athanasios Micheas*+
Companies: University of Missouri, Columbia
Address: Dep. of Statistics, Columbia, MO, 65211-4100,
Keywords: shape analysis ; classification ; MAP estimation ; Monte Carlo simulation ; diagnosing schizophrenia
Abstract:

We discuss classification procedures in a shape analysis context. The usual multivariate techniques of classification, like Fisher discriminant rules, cannot be used in a shape analysis context, since they cannot account for location, dilation, and rotation effects in shapes. We derive discriminants based on likelihood ratios, while considering several models for the data, like the complex Watson and complex Bingham shape distributions. Using MAP (Maximum A Posteriori) estimates of parameters involved, we derive discriminant rules, and calculate misclassification probabilities using Monte Carlo methods. The methods are exemplified through an example, where we are interested in classifying patients into the normal or schizophrenic groups, based on shapes created by MRI images of their brain. Hence, the methods provide us with a new way of diagnosis of this medical condition.

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