Heyman gives an interesting factorization of I-P, where P is the transition probability matrix for an ergodic Markov chain. We show that this factorization.

Jun 20, 1997 · Heyman gives an interesting factorization of I − P, where P is the transition probability matrix for an ergodic Markov Chain.

Let P denote an irreducible positive recurrent infinite stochastic matrix with the unique invariant probability measure π. We consider sequences { P m } m∊N of ...

Heyman gives an interesting factorization of I −P, where P is the transition probability matrix for an ergodic Markov chain. We show that this factorization ...

In this paper, we study Markov chains with infinite state block-structured transition matrices, whose states are partitioned into levels according to the block ...

中国科学院数学与系统科学研究院机构知识库 ; On a decomposition for infinite transition matrices ; Zhao, YQQ; Li, W; Braun, WJ ; 1997 ; 发表期刊, QUEUEING SYSTEMS.

Apr 12, 2022 · How do I raise a matrix to the infinite power? I know that the main method for doing this is by diagonalizing the matrix, but what if I can't?

Yiqiang Q. Zhao, Wei Wayne Li, W. John Braun: On a decomposition for infinite transition matrices. Queueing Syst. Theory Appl. 27(1-2): 127-130 (1997).

Nov 27, 2020 · By raising A to the power of n, I may calculate the transition probability in n steps between any two states. By letting n converge to infinity, ...

Jan 29, 2024 · I want to know how this ends, so all the probabilities of ending in any state, that would look something like this: w := v · ∑ t→∞ (A t )