Hostname: page-component-7479d7b7d-pfhbr Total loading time: 0 Render date: 2024-07-11T10:28:14.331Z Has data issue: false hasContentIssue false

Homogeneous Markov chains by bounded transition matrix

Published online by Cambridge University Press:  14 July 2016

D. J. Hartfiel*
Affiliation:
Texas A&M University
*
Postal address: Department of Mathematics, Texas A&M University, College Station, TX 77 843–3368, USA.

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.

Type
Research Papers
Copyright
Copyright © Applied Probability Trust 1994 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

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, 804825.CrossRefGoogle Scholar
[2] Gantmacher, F. R. (1964) The Theory of Matrices, Vol. 2. Chelsea, New York.Google Scholar
[3] Hartfiel, D. J. (1981) On the limiting set of stochastic products xA1 Am. Proc. Amer. Math. Soc. 81, 201206.Google Scholar
[4] Hartfiel, D. J. (1983) Stochastic eigenvectors for qualitative stochastic matrices. Discrete Math. 43, 191197.Google Scholar
[5] Hartfiel, D. J. (1987) Computing limits of convex sets of distribution vectors xA1Ak. J. Statist. Comput. Simul. 27, 115.Google Scholar
[6] Hartfiel, D. J. (1991) Component bounds for Markov set-chain limiting set. J. Statist. Comput. Simul. 38, 1524.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, 4586.Google Scholar
[8] Seneta, E. (1973) Non-Negative Matrices. Wiley, New York.Google Scholar
[9] Wesselkamper, T. C. (1981) Computer program schemata and processes they generate. IEEE Trans. Software Eng. 8, 412419.Google Scholar