Lecturer |
Zhiqiang Tan 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. | ||||||||||||
Prerequisite |
Stat 593 or equivalent. | ||||||||||||
Textbook | Gelman et al (2014) Bayesian Data Analysis (3rd edition), CRC Press. | ||||||||||||
Topics |
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Exams and Homework |
There will be 2 midterm projects and a final project. Homework will be assigned and collected. | ||||||||||||
Grading |
The final grade will be based on the following components with the weights (corrected March 4):
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Makeup policy |
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. | ||||||||||||
Homework Assignments |
HW 1, HW 2, HW 3, HW 4,
HW 5. 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). | ||||||||||||
Announcements |
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). |