Author's School

Graduate School of Arts & Sciences

Author's Department/Program

Mathematics

Language

English (en)

Date of Award

January 2011

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Chair and Committee

Renato Feres

Abstract

The theory of Markov chains with countable state spaces is a greatly developed and successful area of probability theory and statistics. There is much interest in continuing to develop the theory of Markov chains beyond countable state spaces. One needs good and well motivated model systems in this effort. In this thesis, we propose to produce such systems by introducing randomness into familiar deterministic systems so that we can draw upon the existing: deterministic) results to aid the analysis of our Markov chains. We will focus most heavily on models drawn from Lagrangian mechanical systems with collisions: billiards).

DOI

https://doi.org/10.7936/K7JH3J95

Comments

Permanent URL: http://dx.doi.org/10.7936/K7JH3J95

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