22 Day 22 (April 25)

22.1 Announcements

  • Teaching evaluations

    • There will be several questions
    • Should take about 20 min
    • The information you provide is really helpful

  • Please email me to request a 20-30 min time slot between May 1 and May 9 to give your final presentation. When you email me, please give 3 dates/time that work for you.

  • Peer review is posted and due May 5

22.2 Model selection/comparison

  • What is covered today is selected material from Chs. 13 - 15 of BBM2L.

    • Dr. Gyu Hyeong Goh occasionally teaches a a special topics course on Bayesian model selection (STAT 950)

  • If you have more than one model for a given dataset/problem how do you determine which one(s) to use for prediction and inference?

    • Good resources (here and here)
    • Diversity of approaches from Hooten and Hobbs (2015)

  • Predictive performance metrics

    • Information criteria vs. scoring functions
    • Important characteristics of a predictive distribution (example using Day 14 notes; maximize the sharpness of the predictive distributions, subject to calibration)
    • Good resource (here)

  • Live example using DIC R code

  • Live example using regularization R code

  • Live example using Bayesian model averaging R code