JSM 2003 Online Program

Abstract #302328

This is the preliminary program for the 2003 Joint Statistical Meetings in San Francisco, California. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 2-5, 2003); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

To View the Program:
You may choose to view all activities of the program or just parts of it at any one time. All activities are arranged by date and time.

The views expressed here are those of the individual authors
and not necessarily those of the ASA or its board, officers, or staff.

Back to main JSM 2003 Program page

Activity Number:	254
Type:	Contributed
Date/Time:	Tuesday, August 5, 2003 : 12:00 PM to 1:50 PM
Sponsor:	Section on Bayesian Stat. Sciences
Abstract - #302328
Title:	Bayesian Analysis of Two-Piece Normal Regression Models
Author(s):	Teruo Nakatsuma*+
Companies:	Keio University
Address:	2-15-45 Mita, Minato-ku, Tokyo, 108-8345, Japan
Keywords:	two-piece normal distribution ; regression model ; Markov chain Monte Carlo ; Gibbs sampler ; Hit-and-Run algorithm
Abstract:	This paper develops a Markov chain Monte Carlo method for Bayesian inferences about a linear regression model with a two-piece normal distributed error term, or two-piece normal regression model for short. The two-piece normal distribution is a generalization of the normal distribution. Its advantage over the normal distribution is that it can be asymmetric and thick-tailed but more tractable than other asymmetric distributions. Our sampling algorithm for the two-piece normal regression model is based on the Gibbs sampler and the Hit-and-Run algorithm.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2003 program