This is a preview. Log in through your library . Abstract We have two aims in this paper. First, we generalize the well-known theory of matrix-geometric methods of Neuts to more complicated Markov ...

Abstract Let 𝜉 = {𝜉𝑛}𝑛≥₀ be a Markov chain defined on a probability space (Ω, ℱ, ℙ) valued in a discrete topological space 𝑆 that consists of a finite number of real 𝑑 × 𝑑 matrices. As usual, ...

A Markov chain is a sequence of random variables that satisfies P(X t+1 ∣X t ,X t−1 ,…,X 1 )=P(X t+1 ∣X t ). Simply put, it is a sequence in which X t+1 depends only on X t and appears before X t−1 ...