Bayesian Statistics, Spring 2017

Bayesian Statistics, Spring 2017
STP 598, Course # 14098 XP
class time:T Th 10:30 AM 11:45 AM
class location: Tempe - WXLRA311 01/09 - 04/28(C)


Syllabus

Notes


Project

You can do any applied Bayesian problem you want for the project.

A nice one to try would be to code up the SSVS algorithm and carefully assess the influence of the prior choice on variable selection.
You could use the diabetes data on the webpage and just use the first ten x's. That is, don't bother with the transformations.

There will not be any more homework that you have to hand in, but I encourage you to come to class.
We still have some basic topics you should know about!!


R

The official R introduction:
Introduction to R
Go to The R Project to get the lastest version.

Rob's brief Introduction to R

There a a million books and online stuff.
A nice book is:
"The Art of R Programming", by Norman Matloff.

Note: You will probably want to use R-studio!!!!

Here are three "Rmarkdown quickies" I found on the web.
Let me know if you find better one!!!
rmarkdown1.pdf
rmarkdown2.pdf
The R-studio Cheatsheet
and I like this one too:
rmarkdown-reference.pdf
And how about:
More Rmarkdown from RStudio

To install R under Windows:
   Google "install R under Windows"
   click on "Download R-x.x.x for Windows"
   Click on "Run"


Homework

Homework 0

Get the .Rmd file first.Rmd to compile to pdf and/or html in R-studio.

Homework 1

Homewwork 1
Due Thursday, January 26th.

Homework 2

Homework 2
Due Thursday, February 2.

Homework 3

Homework 3
Due Thursday, February 9.

Homework 4

Homework 4
Due Thursday, February 16.

Homework 5

Homework 5
Due Thursday, March 2.

Homework 6

Homework 6
Due Thursday, March 20.


Log

March 24: Finished MH notes.

February 21: Finished notes on Probit regression.


February 21: Finished notes on Ridge regression and started the notes on Probit regression.

February 2: finished notes on ``More on the multivariate normal''. Next up: ``Markov Chains''.

January 19: We stopped just before the section
"Prediction" in the Normal Mean Notes.
Homework 1 is due next Thursday, January 26th.
Just hand in hard-copy, one per group.

January 26: We looked at the notes ``Canadian Returns'' and ``multivariate change of variable''.
Next we will do ``The Dirichlet Distribution and the multinomial ''.
Homework 2 is due February 2.