Simon Fraser University
Engaging the World

Course Outlines

Spring 2023 - STAT 853 G100

Applications of Statistical Computing (4)

Class Number: 5929

Delivery Method: In Person

Overview

  • Course Times + Location:

    Jan 4 – Apr 11, 2023: Mon, Wed, 10:30 a.m.–12:20 p.m.
    Burnaby

  • Prerequisites:

    STAT 830 or equivalent or permission of instructor.

Description

CALENDAR DESCRIPTION:

An introduction to computational methods in applied statistics. Topics can include: the bootstrap, Markov Chain Monte Carlo, EM algorithm, as well as optimization and matrix decompositions. Statistical applications will include frequentist and Bayesian model estimation, as well as inference for complex models. The theoretical motivation and application of computational methods will be addressed.

COURSE DETAILS:

Course Outline:

This course will focus on Monte Carlo methods:
- Motivation and foundations: review of Bayesian inference, Monte Carlo integration, Importance sampling
- Markov Chain Monte Carlo (MCMC) Methods: general state-space Markov chain theory, Metropolis-Hastings algorithm, Gibbs sampler, Hamiltonian Monte Carlo, Reversible jump MCMC
- Sequential Monte Carlo (SMC) Methods: SMC for state space models, annealed SMC for static problems, Particle Markov Chain Monte Carlo
- Other topics: variational inference, Approximate Bayesian Computation

Grading

  • Assignments 40%
  • Participation/Attendance 20%
  • Project 40%

NOTES:

Above grading is subject to change

Materials

RECOMMENDED READING:

Monte Carlo Statistical Methods, 2nd ed. Authors: Christian Robert and George Casella. Publisher: Springer
ISBN: 9780387212395

Introducing Monte Carlo Methods with R. Authors: Christian Robert and George Casella. Publisher: Springer
ISBN: 978-1-4419-1575-7

The Bayesian Choice, 2nd ed. Author: Christian Robert. Publisher: Springer.
ISBN: 978-0387715988

Monte Carlo theory, methods and examples (2013). Author: Art Owen.
Available from the author's webpage: https://artowen.su.domains/mc/

REQUIRED READING NOTES:

Your personalized Course Material list, including digital and physical textbooks, are available through the SFU Bookstore website by simply entering your Computing ID at: shop.sfu.ca/course-materials/my-personalized-course-materials.

Graduate Studies Notes:

Important dates and deadlines for graduate students are found here: http://www.sfu.ca/dean-gradstudies/current/important_dates/guidelines.html. The deadline to drop a course with a 100% refund is the end of week 2. The deadline to drop with no notation on your transcript is the end of week 3.

Registrar Notes:

ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS

SFU’s Academic Integrity website http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the university community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the university. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the university. http://www.sfu.ca/policies/gazette/student/s10-01.html