JSM 2005 - Toronto

Abstract #303633

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 233
Type: Contributed
Date/Time: Tuesday, August 9, 2005 : 8:30 AM to 10:20 AM
Sponsor: General Methodology
Abstract - #303633
Title: Combining Loglinear Models
Author(s): Lihua Chen*+ and Yuhong Yang
Companies: Iowa State University and University of Minnesota
Address: 15 D SChilletter Village, Ames, IA, 50010, United States
Keywords: model combining ; model selection instability ; loglinear models
Abstract:

We propose a model combining methods for estimating cell probabilities or a missing cell mean in loglinear models. It assigns convex weights to the models based on table splitting, where one subtable is used to estimate the parameters in each model and the other subtable is used to evaluate the likelihood for each model. Estimation with this approach is compared to estimation with model selection and Bayesian model averaging methods via data examples and simulations. The results show the advantage of our model combining approach for dealing with uncertainty in model selection. We derive risk bounds for the combined estimator under both the Kullback- Leibler and squared error loss functions.

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Revised March 2005