A Gibbs Sampling Algorithm for a Changing Regression Model with Pooled Binary Response Data
Sung Won Kang · Communication in Statistics- Theory and Methods · 2007
This article presents a Gibbs Sampling algorithm for a changing regression model with a pooled binary dependent variable. A Gibbs Sampling algorithm for a changing regression model with a continuous dependent variable is extended to binary response data using the chained data augmentation of Tanner (1996 Tanner , M. A. ( 1996 ). Tools for Statistical Inference: Methods for the Exploration of Posterior Distribution and Likelihood Functions. , 3rd ed. New York : Springer . [Google Scholar]). The proposed algorithm is applied to numerical examples with a single change point and multiple change points. The results suggest that this algorithm robustly provides accurate estimates of change points, and that this algorithm also provides sharper estimates of regression parameters when it is applied to a pooled data with a larger cross-section sample size.