1

August 22

The Bayesian Paradigm: Lecture-I
The original article: Bayes (1763)
NY Times article: Adding Art...Science

no HW

Read Sections 1.1, 1.2 & 1.8.1
Read an article by Efron (1986)

2

Aug 24

Prior and Posterior distributions
MC simulation using R: R-Intro manual
An algortihm to compute HDR

use R

Read Section 1.4. Solved in class: 1.38, 1.39, 1.44
Download R and run the code: example1.R
Use the R package hdrcde to compute HDRs

3

Aug 27

Sufficiency and Likelihood principles
An essay on Likelihood principle

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Read Section 1.3. Solved in class: 1.12, 1.16, 1.17
Review of Classical/Frequentist Inference

4

Aug 29

Improper prior distributions
Review of Calculus and Matrices

HW1
(due Sep 5)

Read Section 1.5. Solved in class: 1.47, 1.48, 1.51, 1.53, 1.60
Compute HDR using R codes: hdrbeta.R and hdrgamma.R

5

Aug 31

Problem solving session (Chap. 1)

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Read Section 1.7
Solved in class: Exercises from Lecture-I

6

Sep 3

Labor Day: No class

.

No assignment

7

Sep 5

Prior Information to Distribution: Lecture-II
Principle of maximum entropy

HW2
(due Sep 12)

Read Section 3.1, 3.2.1-3.2.3 HW1 due TODAY!
Generate random samples from Pareto: rpareto.R
Density of Pareto: dpareto.R

8

Sep 7

Some references on choice of priors
Quantifying Prior Information

HWS1
(HW1 solution)

Read Section 3.2.4, 3.3
Some solved examples on improper intergrals

9

Sep 10

Conjugate priors

.

Read Section 3.3

10

Sep 12

Noninformative (NI) priors
A catalog of NI priors

HW3
(due Sep 19)

Read Section 3.5 HW 2 due TODAY!

11

Sep 14

Problem solving session (Chap. 3)
Prior selection using formal rules

HWS2
(HW2 solution)

Read Section 3.7

12

Sep 17

Decision Theory: Lecture III

.

Read Section 2.1
Comparing frequentist risks: frisk.R

13

Sep 19

Risk functions

HW4
(due Sep 26)

Read Section 2.3 HW3 due TODAY!

14

Sep 21

Two optimalities: Admisssibility and minimaxity

HWS3
(HW3 solution)

Read Section 2.4

15

Sep 24

Guest lecture by Eric Belasco

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Modeling ex-ante risk

16

Sep 26

Guest lecture by Dhruv Sharma: Usual loss functions

HW5
(due Oct 3)

Read Section 2.5 HW4 due TODAY!

17

Sep 28

Guest lecture by Suraj Anand: Problem solving session (Chap. 2)

HWS4
(HW4 solution)

Read Section 2.7

18

Oct 1

Point Estimation: Lecture - IV

.

Read Section 4.1
Compare two normnal means: ctnm.R
Compare two binomial means: ctbp.R
Compare two poisson means: ctpi.R

19

Oct 3

Precision of Bayes estimators

HW 6
( due Oct 17)

Read Section 4.4 HW 5 due TODAY!

20

Oct 5

Review problems for midterm

HWS5

Read Lecture slides I-III and Chapters 1-3
R codes for HWS5: HW5code.R

21

Oct 8

Midterm Exam: 05:00-07:00 p.m. (PT 208)

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Syllabus: Chapters 1-3 (Summary of grades)

22

Oct 10

The Normal and t Model
For multivariate normal or t use the package mvtnorm in R

no HW

Read Chapter 4

23

Oct 12

Fall break: No class

.

No assignments

24

Oct 15

Test of hypotheses: Lecture - V
Project description

Project (abstract due Nov 13)

Read Section 5.2
A collection of Data sets: DASL (More about Project)

25

Oct 17

Bayes factors and Jeffreys scale of evidence

HW7
(due Oct 24)

Read Section 5.2.6 HW6 due TODAY! (postponed to Friday)
Compute Bayesian p-value: bpvalue.R

26

Oct 19

Credible regions

HWS6

Read Section 5.5.1 (HW6 due TODAY! HW6code.R)
Compute HDR using R codes: hdrbeta.R and hdrgamma.R

27

Oct 22

Bayesian calculations: Lecture VI

.

Read Section 6.2
Examples with R Session-I

28

Oct 24

Monte Carlo methods

HW8
(due Oct 31)

Read Section 6.2.2 HW 7 due TODAY!
Sample R code for rejection sampling: rejsam.R

29

Oct 26

Asymptotic approximations

HWS7

Read Section 6.2.3
Normal approximation to Beta: betanormal.R
R codes for HWS7: HW7code.R

30

Oct 29

Markov Chain Monte Carlo methods

.

Read Section 6.3
Markov Chains

31

Oct 31

An MCMC tutorial

HW9
(due Nov 7)

Read Section 6.3.2
HW8 due TODAY!

32

Nov 2

Guest lecture by Brian Reich: callbugs.R and bugs_code.txt

HWS8
(HW8 solution)

Read Section 6.3.4
R codes for HWS8: HW8code.R

33

Nov 5

Introduction to WinBUGS

use BUGS

Read WinBUGS manual

34

Nov 7

WinBUGS examples
Comparing clouds: Clouds.odc
Vaccine trials: Vaccine.odc
US temperatures: Temperatures.odc

HW10
(due Nov 14)

See WinBUGSexamples.txt HW9 due TODAY!
Data file: JanTemp.txt

35

Nov 9

Slice sampling: Examples

HWS9

Read Section 6.5
R codes for HWS9: HW9code.R

36

Nov 12

R2WinBUGS demo

project abstract

Read Section 10.2 Project abstract due TODAY!

37

Nov 14

Computational issues

HW11
(due Nov 28)

Read Section 10.2.4 HW10 due TODAY!
Data set for HW11: egyptianskulls.txt
Data info: Egyptian Skull development

38

Nov 16

Hierarchical Bayes procedures

HWS10
(HW10 solution)

Read Section 10.3
R codes for HWS10: HW10code.R

39

Nov 19

Empirical Bayes

.

Read Section 10.4

40

Nov 21

Thanksgiving break; No classes

no HW

No assignments

41

Nov 23

Thanksgiving break: University closed

.

No assignments

42

Nov 26

Examples of HB & EB

.

Read Section 10.4.2

43

Nov 28

Examples of non-standard models

HW12
(due Dec 5)

Read Section 10.6 HW11 due TODAY!
Non-standard examples: IllustratedExamples.odc

44

Nov 30

More examples...

HWS11

Read Section 10.6
Codes for HWS11: HW11code.zip

45

Dec 3

Nonparametric Bayes (VERY brief intro)

.

Read Bayesian function estimation

46

Dec 5

Project presentations

HWS12

Teams: 1-3 (morning) and 4-6 (afternoon)
HW12 due TODAY!
Codes for HWS11: HW12code.zip

47

Dec 7

Project presentations

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Teams: 7-9(morning) and 10-11 (aftertoon)