Description
Basic ideas and algorithms of Monte Carlo; simulation of basic stochastic processes. Brownian motion and the Poisson process, applications to financial modelling, queueing theory. Output analysis; variance reduction. Markov chain Monte Carlo methods; Gibbs sampling, simulated annealing and Metropolis-Hastings samplers with applications.
Prerequisites
- Prerequisite(s): STAT 3558 , or a grade of B or higher in STAT 3508 , or permission of the School.
Conditions and arrangements
- Precludes additional credit for Precludes additional credit for STAT 3555 (no longer offered).
- Prerequisite(s): STAT 3558 , or a grade of B or higher in STAT 3508 , or permission of the School.
- Lectures three hours a week, tutorial/laboratory one hour a week.
Reference text in its original language
Basic ideas and algorithms of Monte Carlo; simulation of basic stochastic processes. Brownian motion and the Poisson process, applications to financial modelling, queueing theory. Output analysis; variance reduction. Markov chain Monte Carlo methods; Gibbs sampling, simulated annealing and Metropolis-Hastings samplers with applications.
- Prerequisite(s): STAT 3558 , or a grade of B or higher in STAT 3508 , or permission of the School.
- Precludes additional credit for Precludes additional credit for STAT 3555 (no longer offered).
- Lectures three hours a week, tutorial/laboratory one hour a week.
Sources and references
Dates and sources are retained to help you verify the information. Translations are provided to facilitate reading; the official source governs conditions and requirements.
Source reference : https://calendar.carleton.ca/undergrad/courses/STAT/