Matrix Analysis for Continuous-Time Markov Chains

IF 0.8 Q2 MATHEMATICS

Special Matrices Pub Date : 2021-01-01 DOI:10.1515/spma-2021-0157

H. Le, M. Tsatsomeros

引用次数: 3

Abstract

Abstract Continuous-time Markov chains have transition matrices that vary continuously in time. Classical theory of nonnegative matrices, M-matrices and matrix exponentials is used in the literature to study their dynamics, probability distributions and other stochastic properties. For the benefit of Perron-Frobenius cognoscentes, this theory is surveyed and further adapted to study continuous-time Markov chains on finite state spaces.

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连续时间马尔可夫链的矩阵分析

连续时间马尔可夫链具有随时间连续变化的转移矩阵。经典的非负矩阵、m矩阵和矩阵指数理论在文献中被用来研究它们的动力学、概率分布和其他随机性质。为了使Perron-Frobenius专家受益，我们对这一理论进行了研究，并将其进一步应用于有限状态空间上的连续时间马尔可夫链的研究。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Special Matrices MATHEMATICS-

CiteScore

1.10

自引率

20.00%

发文量

审稿时长

8 weeks

期刊介绍： Special Matrices publishes original articles of wide significance and originality in all areas of research involving structured matrices present in various branches of pure and applied mathematics and their noteworthy applications in physics, engineering, and other sciences. Special Matrices provides a hub for all researchers working across structured matrices to present their discoveries, and to be a forum for the discussion of the important issues in this vibrant area of matrix theory. Special Matrices brings together in one place major contributions to structured matrices and their applications. All the manuscripts are considered by originality, scientific importance and interest to a general mathematical audience. The journal also provides secure archiving by De Gruyter and the independent archiving service Portico.