Statistics 251b/551b (Spring 1999)
A study of random processes, including Markov chains, Markov random
fields, martingales, random walks, Brownian motion and diffusions.
Introduction to certain modern techniques in probability such as
coupling and large deviations.
Applications to image reconstruction,
Bayesian statistics, finance, probabilistic analysis of algorithms,
genetics and evolution.
After Statistics 241a
Instructor: David Pollard
(24 Hillhouse Avenue;
Office hours: Tuesday 9:30--11:00 (or catch me straight after
TA: Andrew Carter
Office hours: Monday 2:30-3:30 (room 305 of 24 Hillhouse)
Monday, Wednesday 1:00 - 2:15 at WLH 207
A knowlege of elementary probability theory at the level of Statistics 241.
See some of my notes from 241 for a brief summary of facts about
and conditional expectations.
The course will be based on a
book manuscript being prepared by Joe Chang.
I expect to cover only the following topics from the
outline prepared by Joe:
If time permits I might also cover parts of
- Markov chains
- Poisson processes
- Markov random fields and hidden Markov models
- Brownian motion
- Diffusions, stochastic calculus, stochastic differential equations
- Likelihood ratios and extremes
Most of the final grade will be based on the weekly homework assignments.
A small project will take the place of a final exam.
Boxplots of homework scores.
Email correspondence regarding homeworks and
other aspects of the course.
---> Statistics 251