Statistics 221 - Statistical Computing Methods

Instructor: Mark Irwin
Office: Science Center 235
Phone: 617-495-5617
E-mail: irwin@stat.harvard.edu
Lectures: Wednesday and Friday, 3:30 - 5:00, Science Center 102 B
Office Hours: Tuesday 1:30 - 2:30, Thursday 10:30 - 11:30, or by appointment.
Syllabus: PDF version of the syllabus

Teaching Fellow: Taeyoung Park (tpark@stat.harvard.edu)
Office Hour: Friday 12:00 - 1:00, Science Center 705 (Department library).
Section: Thursday 5:00 - 6:00, Science Center 109.

A study of computing methods commonly used in statistics. Topics include generation of random numbers, Monte Carlo methods, optimization methods, numerical integration, resampling methods such as the Bootstrap and the Jackknife, and advanced Bayesian computational tools such as the Gibbs sampler, Metropolis Hastings, the method of auxiliary variables, marginal and conditional data augmentation, slice sampling, exact sampling, and reversible jump MCMC. Computer programming exercises apply the methods discussed in class.

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Solutions

Solutions for the first two assignments have been added to the Assignments page.

Department of Statistics Harvard University

Copyright 2004 by Mark E. Irwin