JSM 2005 - Toronto

JSM Activity #363

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); 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.


The Program has labeled the meeting rooms with "letters" preceding the name of the room, designating in which facility the room is located:

Minneapolis Convention Center = “MCC” Hilton Minneapolis Hotel = “H” Hyatt Regency Minneapolis = “HY”

Back to main JSM 2005 Program page



Legend: = Applied Session, = Theme Session, = Presenter
Add To My Program
363 Applied Session Theme Session Wed, 8/10/05, 8:30 AM - 10:20 AM MCC-209 AB
Bayesian Modeling and Inference - Contributed - Papers
Section on Bayesian Statistical Science
Chair(s): Patrick J. Wolfe, Harvard University
     8:35 AM   On the Mixture of Skew Normal DistributionsJack C. Lee, National Chiao-Tung University; Tsung-I Lin, Tunghai University
     8:50 AM   A Doubly Nested Hidden Markov Model for Internet Browsing BehaviorSteven Scott, University of Southern California
     9:05 AM   An Efficient Mixture-based Shrinkage Estimator: A Monte Carlo AnalysisWilliam Bolstad, University of Waikato
     9:20 AM   Estimation of Bayesian Hierarchical Models with ARIMA NoiseMiguel Arranz, Bayes Inference, S. A.
     9:35 AM   Bayesian Analysis of the Computer Model ValidationFei Liu, Duke University
     9:50 AM   Bayesian Inference with Latent Variable ModelsEric Loken, The Pennsylvania State University
     10:05 AM   Posterior Propriety for Hierarchical Models with Log-concave Likelihoods, Including Hierarchical Generalized Linear ModelsSarah Michalak, Los Alamos National Laboratory; Carl N. Morris, Harvard University
 

JSM 2005 For information, contact jsm@amstat.org or phone (888) 231-3473. If you have questions about the Continuing Education program, please contact the Education Department.
Revised March 2005