Displaying similar documents to “Covariance and relaxation time in finite Markov chains.”

The Kendall theorem and its application to the geometric ergodicity of Markov chains

Witold Bednorz (2013)

Applicationes Mathematicae

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We give an improved quantitative version of the Kendall theorem. The Kendall theorem states that under mild conditions imposed on a probability distribution on the positive integers (i.e. a probability sequence) one can prove convergence of its renewal sequence. Due to the well-known property (the first entrance last exit decomposition) such results are of interest in the stability theory of time-homogeneous Markov chains. In particular this approach may be used to measure rates of convergence...

Why the Kemeny Time is a constant

Karl Gustafson, Jeffrey J. Hunter (2016)

Special Matrices

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We present a new fundamental intuition forwhy the Kemeny feature of a Markov chain is a constant. This new perspective has interesting further implications.

On convergence in distribution of the Markov chain generated by the filter kernel induced by a fully dominated Hidden Markov Model

Thomas Kaijser

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Consider a Hidden Markov Model (HMM) such that both the state space and the observation space are complete, separable, metric spaces and for which both the transition probability function (tr.pr.f.) determining the hidden Markov chain of the HMM and the tr.pr.f. determining the observation sequence of the HMM have densities. Such HMMs are called fully dominated. In this paper we consider a subclass of fully dominated HMMs which we call regular. A fully dominated,...

A family of stationary processes with infinite memory having the same p-marginals. Ergodic and spectral properties

M. Courbage, D. Hamdan (2001)

Colloquium Mathematicae

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We construct a large family of ergodic non-Markovian processes with infinite memory having the same p-dimensional marginal laws of an arbitrary ergodic Markov chain or projection of Markov chains. Some of their spectral and mixing properties are given. We show that the Chapman-Kolmogorov equation for the ergodic transition matrix is generically satisfied by infinite memory processes.

Technical comment. A problem on Markov chains

Franco Giannessi (2002)

RAIRO - Operations Research - Recherche Opérationnelle

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A problem (arisen from applications to networks) is posed about the principal minors of the matrix of transition probabilities of a Markov chain.