Description
- Abstract:
- Recently, some researchers have attempted to exploit state-aggregation techniques to compute stable distributions of high-dimensional Markov matrices. While these researchers have devised an efficient, recursive algorithm, their results are only approximate. We improve upon past results by presenting a novel state aggregation technique, which we use to give the first (to our knowledge) scalable, exact algorithm for computing the stochastically stable distribution of a perturbed Markov matrix. Since it is not combinatorial in nature, our algorithm is computationally feasible even for high-dimensional models.
- Notes:
- Thesis (Ph.D.) -- Brown University (2009)
Access Conditions
- Rights
- In Copyright
- Restrictions on Use
- Collection is open for research.
Citation
Wicks, John Randolph,
"An Algorithm to Compute the Stochastically Stable Distribution of a Perturbed Markov Matrix"
(2009).
Computer Science Theses and Dissertations.
Brown Digital Repository. Brown University Library.
https://doi.org/10.7301/Z09Z93BN
Relations
Collection:
-
Computer Science Theses and Dissertations
Theses and Dissertations for the Computer Science department....