602.spring07
#### Probability Coupling (STAT 602b)

Instructor: David Pollard

Time: Tuesday, Thursday 10:30-12:00

Place: 24 Hillhouse main classroom

Some of the most striking advances in probability theory have involved
coupling: the representation of distributional relationships by means of
deterministic properties of specially created joint distributions. The
course explores the method through applications such as quantile
coupling; almost sure representations for convergence in distribution;
problems of mass transportation; Strassen's theorem and stochastic
ordering; Wasserstein distances; rapidly mixing Markov chains;
interacting systems of particles; the Hungarian (KMT) strong
approximations; Poisson approximation; distances between statistical
models (Blackwell/Le Cam theory). Acquaintance with measure theoretic
probability would be an advantage, but all topics are made accessible to
students with a knowledge of probability at the level of STAT 541a.
Apache/2.2.3 (Red Hat) Server at www.stat.yale.edu Port 80