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Markov Chains with finite convergence time
- Source :
- Stochastic Processes and their Applications. (3):247-253
- Publisher :
- Published by Elsevier B.V.
-
Abstract
- We study the properties of finite ergodic Markov Chains whose transition probability matrix P is singular. The results establish bounds on the convergence time of Pm to a matrix where all the rows are equal to the stationary distribution of P. The results suggest a simple rule for identifying the singular matrices which do not have a finite convergence time. We next study finite convergence to the stationary distribution independent of the initial distribution. The results establish the connection between the convergence time and the order of the minimal polynomial of the transition probability matrix. A queuing problem and a maintenance Markovian decision problem which possess the property of rapid convergence are presented.
- Subjects :
- Statistics and Probability
Discrete mathematics
Stationary distribution
Markov kernel
null space
Markov chain
Markov chains
Applied Mathematics
Stochastic matrix
eigenvalues
Markov decision problem
convergence time
accessibility
Continuous-time Markov chain
minimal polynomial
Matrix analytic method
Modelling and Simulation
Modeling and Simulation
leading vectors
Applied mathematics
Markov property
Compact convergence
Mathematics
Subjects
Details
- Language :
- English
- ISSN :
- 03044149
- Issue :
- 3
- Database :
- OpenAIRE
- Journal :
- Stochastic Processes and their Applications
- Accession number :
- edsair.doi.dedup.....1bf08f36345a1e072a2c9b47277e0f37
- Full Text :
- https://doi.org/10.1016/0304-4149(78)90044-3