Reading 10: MCMC Inference

Reading 10: MCMC Inference#

For the class on Wednesday, February 14th

Reading assignments#

  1. Read the following sections of [ICVG20]:

    • Sec. 5.4 “Bayesian Model Selection”

      • Lead paragraphs (text between the headings of Sec. 5.4 and Sec. 5.4.1)

      • Subsection 5.4.3 “Information Criteria”

    • Sec. 5.6.2 “Parameter Estimation for the Binomial Distribution”

    • Sec. 5.8 “Numerical Methods for Complex Problems (MCMC)”

      • Lead paragraphs (text between the headings of Sec. 5.8 and Sec. 5.8.1)

      • Sec. 5.8.1 “Markov Chain Monte Carlo”

      • Sec. 5.8.2 “MCMC Algorithms”

      • Sec. 5.8.4 “Example: Model Selection with MCMC”



Submit your answer on Canvas. Due at noon, Wednesday, February 14th.

  1. List anything from your reading that confuses you. Explain why they confuse you. If nothing confuses you, briefly summarize what you have learned from this reading assignment.

  2. Use your own words to briefly explain (around or less than 100 words) what a jump kernel (or transition kernel) is. What was the jump kernel we used in our MCMC simulation for the Ising model?

Discussion Preview#


We will discuss the following questions in class. They are included here so that you have a chance to think about them before class. You need not submit your answers as part of this assignment.

We will learn how to use emcee and go through this example in detail.