Recurrent Class: Set of state inA(i)form a recurrent class. States inA(i)are accessible from each other, no states outsideA(j)is accessible from them. For a recurrent statei, we haveA(i)=A(j)ifjbelongs toA(i). And we drived the Markov chain decomposition law: A Markov chain can ...
Clearly, the sum of each row of P is 1. A well-known theorem of Markov chains states that the probability of the system being in state j after k time periods, given that the system begins in state i, is the (i, j) entry of Pk. A common question arising in Markov-chain ...
In this work, we propose to combine the standard coupling from the past and the multi-gamma coupler algorithms to allow perfect simulation of the steady-state probability of a Markov chain (MC), whose state space E is composed of a continuous part C and a finite part D . We show that ...
Fourneau, "Iterative component-wise bounds for the steady-state distribution of a Markov chain," Numerical Linear Algebra with Applications, vol. 18, no. 6, pp. 1031-1049, 2011.Busic, A., Fourneau, J.-M.: Iterative component-wise bounds for the steady-state distribution of a markov chain...
In this paper, we develop a continuous-time Markov chain model to describe the radio spectrum usage, and derive the transition rate matrix for this model. In addition, we perform steady-state analysis to analytically derive the probability state vector. The proposed model and derived expressions ...
In this paper we study Monte Carlo estimators based on the likelihood ratio approach for steady-state sensitivity. We first extend the result of Glynn and Olvera-Cravioto [doi:doi: 10.1287/stsy.2018.002 ] to the setting of continuous time Markov chains with a countable state space which include...
probabilities depend not only on the current state of a node itself, but also on the states of all the nodes to which it is connected. The overall system evolves according to a global Markov Chain whose state space dimension is the product of states describing each node. When dealing with ...
4. Some Improvements for the Computation of the Steady-State Distribution of a Markov Chain by Monotone Sequences of Vectors [C] . Jean-Michel Fourneau, Franck Quessette Analytical and stochastic modeling techniques and applications. . 2012 机译:向量单调序列对马尔可夫链稳态分布计算的一些改进 ...
Steady-State Theory refers to a mathematical concept associated with stationary Markov processes, characterizing nonequilibrium steady states in terms of time irreversibility, breakdown of detailed balance, free energy dissipation, and positive entropy production rate. AI generated definition based on: Physic...
This paper employs Markov chain to the evaluation of steady state of an incineration process. Novel definition of transition probability matrix of FACS is presented. Steady state vector of Markov chain for incineration process is determined and graph of convergence of its norm difference is presented...