Recursive algorithm for the fundamental/group inverse matrix of a Markov chain from an explicit formula

SIAM Journal on Matrix Analysis and Applications

Volumn 23, Issue 1, 2002, Pages 209-224

  Sonin, Isaac ^a   Thornton, John ^a  

^a UNIVERSITY OF NORTH CAROLINA AT CHARLOTTE   (United States)

Author keywords

Fundamental group inverse matrix; GTH S algorithm; Markov chain; Recursive algorithm

Indexed keywords

EID: 0036056004     PISSN: 08954798     EISSN: None     Source Type: Journal    
DOI: 10.1137/S0895479899351234     Document Type: Article

References (32)

1. Regenerative analysis and steady-state distributions for Markov chains
2. Means and variances in Markov reward systems
3. Comparison of some direct methods for computing stationary distributions of Markov chains
4. Accurate computation of the fundamental matrix of a Markov chain
5. What is fundamental for Markov chains: First passage times, fundamental matrices, and group generalized inverses
6. Numerical solution of linear equations arising in Markov chain models
7. Overcoming instability in computing the fundamental matrix for a Markov chain
8. Numerical computation of mean passage times and absorption probabilities in Markov and semi-Markov models
9. Reduced systems algorithms for Markov chains
10. Generalized inverses in discrete time Markov decision processes
11. The role of the group generalized inverse in the theory of finite Markov chains
12. Linear algebra, Markov chains, and queueing models
13. Entrywise perturbation theory and error analysis for Markov chains
14. A Markov partitioning algorithm for computing steady-state probabilities
15. Matrix inversion by augmentation and reduction
16. Computing absorption probabilities for a Markov chain
17. Computing the fundamental matrix for a reducible Markov chain
18. Computing mean first passage times for a Markov chain
19. A partitioning algorithm for solving systems of linear equations
20. Two simple theorems in the problems of optimal stopping
21. The state reduction and related algorithms and their applications to the study of Markov chains, graph theory and the optimal stopping problem
22. The Elimination algorithm/or the problem of optimal stopping
23. The elimination algorithm and its applications
24. Computational properties of algorithm REFUND/or the fundamental/group inverse matrix of a Markov chain
25. Iterative methods/or computing stationary distributions of nearly completely decomposable Markov chains
26. Numerical methods/or computing stationary distributions o/finite irreducible Markov Chains