Markov Set-Chains
Hartfiel, Darald J.
Markov Set-Chains [electronic resource] / by Darald J. Hartfiel. - VIII, 132 p. online resource. - Lecture Notes in Mathematics, 1695 0075-8434 ; . - Lecture Notes in Mathematics, 1695 .
Stochastic matrices and their variants -- to Markov set-chains -- Convergence of Markov set-chains -- Behavior in Markov set-chains.
In this study extending classical Markov chain theory to handle fluctuating transition matrices, the author develops a theory of Markov set-chains and provides numerous examples showing how that theory can be applied. Chapters are concluded with a discussion of related research. Readers who can benefit from this monograph are those interested in, or involved with, systems whose data is imprecise or that fluctuate with time. A background equivalent to a course in linear algebra and one in probability theory should be sufficient.
9783540687115
10.1007/BFb0094586 doi
Distribution (Probability theory.
Matrix theory.
Discrete groups.
Computer science.
Probability Theory and Stochastic Processes.
Linear and Multilinear Algebras, Matrix Theory.
Convex and Discrete Geometry.
Mathematical and Computational Biology.
Math Applications in Computer Science.
QA273.A1-274.9 QA274-274.9
519.2
Markov Set-Chains [electronic resource] / by Darald J. Hartfiel. - VIII, 132 p. online resource. - Lecture Notes in Mathematics, 1695 0075-8434 ; . - Lecture Notes in Mathematics, 1695 .
Stochastic matrices and their variants -- to Markov set-chains -- Convergence of Markov set-chains -- Behavior in Markov set-chains.
In this study extending classical Markov chain theory to handle fluctuating transition matrices, the author develops a theory of Markov set-chains and provides numerous examples showing how that theory can be applied. Chapters are concluded with a discussion of related research. Readers who can benefit from this monograph are those interested in, or involved with, systems whose data is imprecise or that fluctuate with time. A background equivalent to a course in linear algebra and one in probability theory should be sufficient.
9783540687115
10.1007/BFb0094586 doi
Distribution (Probability theory.
Matrix theory.
Discrete groups.
Computer science.
Probability Theory and Stochastic Processes.
Linear and Multilinear Algebras, Matrix Theory.
Convex and Discrete Geometry.
Mathematical and Computational Biology.
Math Applications in Computer Science.
QA273.A1-274.9 QA274-274.9
519.2