Welcome to Statistics

Welcome to STAT 825, Advanced Bayesian Modeling and Analysis

Prof. Prem Goel

   Office: 204C Cockins Hall, 1958 Neil Ave.
   Tel.: 292-8110
   E-mail: Prem Goel
   OFFICE HOURS: Tues, Thur 2:00-3:30PM, or BY APPOINTMENT.

RECENT ANNOUNCEMENTS/REMINDERS:

1) The project presentations and Final Report are due by 3:00PM, Wednesday, June 8, by so that I can post them in time for presentations on Thursday, June 9th, 11:30AM-1:30PM.

2) Solutions to Home Work Assignments 3 and 4 are now posted on this site.

COURSE INFORMATION:

● SYLLABUS

● READING MATERIAL:

1) JASA 2000 Bayesian Statitics Review Paper, By James Berger

2) Dawning of the age of Stochasticity, By David Mumford

3) Software Review of 'Ox' - A new tool for Bayesian Analysis

4) Bayesian Exploratory Data Analysis, By MacEachern and Peruggia

5) Web LINKS for Monty Hall and Prisoner's Dilemma Problems

6) Hierarchical Models-Bayesian Modeling of Gene Expression Data by Ibrahimi et al.

7) Posterior Predictive Model Checks for Disease Mapping by Stern and Cressie.

8) Explaining the Gibbs Sampler by Casella and George.

9) Bayesian Approach to Transformation to Normality by Perrichi.

10) Markov Chain Monte Carlo by L. Tierney

11) Understanding Metropolis-Hastings Algorithm by Chib and Greenberg

12) Bayesian Model Selection by Kadane

10) Markov Chain Monte Carlo by L. Tierney

11) Understanding Metropolis-Hastings Algorithm by Chib and Greenberg

13) Optimal Predictive Model Selection by Berger et al

14) Model Selection Review by Wasserman

● LECTURE SLIDES:

1) Bayesian Analysis in Multiparameter problems

2) Continuation of Multiparameter problems

3) Large Sample Bayesian Inference

● HOME WORK ASSIGNMENTS + SOLUTIONS:

1) Home Work Assignment # 1

2) Home Work Assignment #2

3) Comments on HW #2

4) Home Work Assignment #3

5) Home Work Assignment #4

6) Solution to Home Work Assignment # 1

7) Solution to Home Work Assignment # 2

8) Solution to Home Work Assignment # 3

9) Solution to Home Work Assignment # 4

● PROJECTS RELATED INFO:

1) LINKS for DATA SOURCES

● None of the Prelim Reports, Presentations and Final Reports mentioned below involve Bayesian Analysis. These are meant as Examples of the Format, rather than contents.

2) Project-Preliminary Report (EXAMPLE 1)

3) Project-Preliminary Report (EXAMPLE 2)

4) Project-Preliminary Report (EXAMPLE 3)

5) Project-Preliminary Report (EXAMPLE 4)

6) Classification for Functional Data(Presentation-Example 1)

7) Character Recognition(Presentation-Example 2)

8) Credit Card Approval(Presentation-Example 3)

9) Statistical Learning for DNA(Presentation-Example 4)

10) Diabetes Among Pima Indian Women(Presentation-Example 5)

11) Subspace Methods in Face Recognition(Presentation-Example 6)

12) Final Report-Example 1

13) Final Report-Example 2