The Ergodic Theorem and Markov Chain Strong Laws

Loading...

View/Download File

HUANG_umn_0130M_16371.pdf (895.66 KB)

Persistent link to this item

https://hdl.handle.net/11299/174784

Statistics

View Statistics

Journal Title

Journal ISSN

Volume Title

Title

The Ergodic Theorem and Markov Chain Strong Laws

Authors

Huang, Yan

Published Date

2015-08

Publisher

Type

Thesis or Dissertation

Abstract

The purpose of this paper is to explain the pointwise Ergodic Theorem and then to apply it to stationary Markov Chains. The Ergodic Theorem is a theorem which shows that the time-averages of a stationary sequence of random variables converge almost surely, and also gives a way to evaluate the limit of these averages. In the setting of Markov chains, the Ergodic Theorem can be used to obtain an important convergence fact about Markov chains.

Keywords

Ergodic Theorem

Markov Chains

Strong Law

Description

University of Minnesota M.S. thesis. August 2015. Major: Mathematics. Advisor: John Baxter. 1 computer file (PDF); iv, 35 pages.

Related to

Replaces

License

Collections

Master's Theses (Plan A and Professional Engineering Design Projects)

Series/Report Number

Funding information

Isbn identifier

Doi identifier

Previously Published Citation

Suggested citation

Huang, Yan. (2015). The Ergodic Theorem and Markov Chain Strong Laws. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/174784.

Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.