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Homogeneous Markov chains by bounded transition matrix
Part of:
Markov processes
Published online by Cambridge University Press: 14 July 2016
Abstract
Let A be a stochastic matrix and ε a positive number. We consider all stochastic matrices within ε of A and their corresponding stochastic eigenvectors. A convex polytope containing these vectors is described. An efficient algorithm for computing bounds on the components of these vectors is also given. The work is compared to previous such work done by the author and by Courtois and Semai.
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- Research Papers
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- Copyright © Applied Probability Trust 1994
References
[1]
Courtois, P. J. and Semal, P. (1984) Bounds for the positive eigenvalues of nonnegative matrices and their approximations by decomposition. J. Assoc. Comput. Mach. 31, 804–825.CrossRefGoogle Scholar
[3]
Hartfiel, D. J. (1981) On the limiting set of stochastic products xA1
Am. Proc. Amer. Math. Soc. 81, 201–206.Google Scholar
[4]
Hartfiel, D. J. (1983) Stochastic eigenvectors for qualitative stochastic matrices. Discrete Math. 43, 191–197.Google Scholar
[5]
Hartfiel, D. J. (1987) Computing limits of convex sets of distribution vectors xA1Ak. J. Statist. Comput. Simul. 27, 1–15.Google Scholar
[6]
Hartfiel, D. J. (1991) Component bounds for Markov set-chain limiting set. J. Statist. Comput. Simul. 38, 15–24.Google Scholar
[7]
Rothblum, U. G. and Tan, C. P. (1985) Upper bounds on the maximal modulus of subdominant eigenvalues of nonnegative matrices. Linear Algebra Appl.
66, 45–86.Google Scholar
[9]
Wesselkamper, T. C. (1981) Computer program schemata and processes they generate. IEEE Trans. Software Eng. 8, 412–419.Google Scholar