Abstract. Heyman gives an interesting factorization of I-P, where P is the transition probability matrix for an ergodic Markov chain. We show that this ...
Jun 20, 1997 · Heyman gives an interesting factorization of I − P, where P is the transition probability matrix for an ergodic Markov Chain.
Heyman gives an interesting factorization of I −P, where P is the transition probability matrix for an ergodic Markov chain.
In this paper, we study Markov chains with infinite state block-structured transition matrices, whose states are partitioned into levels according to the block ...
Aug 1, 2022 · I understand that the general purpose of these equations is to show that the matrix P(t) can be factorized using Eigenvalue Decomposition - but ...
Bibliographic details on On a decomposition for infinite transition matrices.
[8] Y.Q. Zhao, W. Li and W.J. Braun, Infinite block-structured transition matrices and their properties, Adv. Appl. Prob., (1998) to appear.
Feb 7, 2021 · My friend pointed out the following trick. Eigendecomposition means we can write the original matrix as. V x D x V^-1.
Sep 12, 2012 · If the state space S is countably infinite, finite sums are replaced by sums of convergent series and square matrices of finite size by arrays ...
Apr 3, 2022 · As the number of transitions increases, the probabilities in the matrix converge to certain values, known as the steady-state probabilities.
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