University of Calgary

STAT 631 - Computational Statistics - Winter 2020

Unconstrained optimization methods, simulation and random number generation, Bayesian inference and Monte Carlo methods, Markov chain Monte Carlo, non-parametric inference, classical inference and other topics. An emphasis will be placed on computational implementation of algorithms.
This course may not be repeated for credit.

Hours

  • H(3-0)

Prerequisite(s)

  • Admission to a graduate program in Mathematics and Statistics or consent of the Department.
Syllabus

Sections

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