Office: 459 Hill Center
Email: ztan at stat.rutgers.edu
Lectures: MW 1:40-3:00PM, HIL 522
Office hours: TH 1:00-2:00PM.
Stat 593 or equivalent. |
|Textbook||Gelman et al (2014) Bayesian Data Analysis (3rd edition), CRC Press.|
|Exams and Homework||
There will be 2 midterm projects and a final project.|
Homework will be assigned and collected.
The final grade will be based on the following components with the weights (corrected March 4):|
Make-up exams will only be given if written documentation of a major outside circumstance is provided by a dean or a doctor.|
Students who miss exams without presenting proper documentation in a timely manner will receive a grade of zero.
HW 1, HW 2, HW 3, HW 4,
Selected solution to HW 1.
Here is Gelman et al. (2008).
Here is Karim & Zeger (1992). The dataset is here.
Here is Booth & Hobert (1999).
Posted Feb 12: |
R codes for Metropolis sampling (here) and Gibbs sampling (here) from bivariate normal distributions.
Posted Feb 18, corrected March 4:
R codes for Gibbs sampling (here) for posterior simulation in the eight-school example.
Posted Feb 23:
R codes for Gibbs sampling (here) and Metropolis sampling (here)for posterior simulation in the coagulation example.
Posted March 4:
R codes for parameter-expanded Gibbs sampling (here) for posterior simulation in the eight-school example.
Posted March 25, revised Apr 1:
R codes for the presidential election example (here).
The datasets are here and here.
Posted Apr 16:
R codes for logit and probit regression (here and here).
The dataset is here.
Posted Apr 22:
R codes for the salamander example (here).
Posted May 7:
R codes for the eight-school example, with model checking and comparison (here).