Dissertation
Matrix Analysis Primer for Inhomogeneous Markov Chains
Doctor of Philosophy (PhD), Washington State University
01/2020
Handle:
https://hdl.handle.net/2376/116722
Abstract
Inhomogeneous Markov chains have transition matrices that vary in time. Our interest is to study their dynamics and probability distribution vectors as functions of time. Classical theory of nonnegative matrices, M-matrices and their association to homogeneous Markov chains is extended and adapted to study inhomogeneous Markov chains on finite state spaces.
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Details
- Title
- Matrix Analysis Primer for Inhomogeneous Markov Chains
- Creators
- Hung Van Le
- Awarding Institution
- Washington State University
- Academic Unit
- Mathematics and Statistics, Department of
- Theses and Dissertations
- Doctor of Philosophy (PhD), Washington State University
- Number of pages
- 48
- Identifiers
- 99900581609401842
- Language
- English
- Resource Type
- Dissertation