In probability, a discrete-time Markov chain (DTMC) is a sequence of random variables, known as a stochastic process, in which the value of the next variable...

transition is to be made, the process moves according to the jump chain, a discrete-time Markov chain with stochastic matrix: [ 0 1 2 1 2 1 3 0 2 3 5 6 1 6 0 ]...

the chain moves state at discrete time steps, gives a discrete-time Markov chain (DTMC). A continuous-time process is called a continuous-time Markov chain...

X_{n}} in the Markov renewal process is a discrete-time Markov chain. In other words, if the time variables are ignored in the Markov renewal process...

Absorbing Markov chain Continuous-time Markov chain Discrete-time Markov chain Nearly completely decomposable Markov chain Quantum Markov chain Telescoping...

In statistics, Markov chain Monte Carlo (MCMC) is a class of algorithms used to draw samples from a probability distribution. Given a probability distribution...

Markov chains, there can be continuous-time absorbing Markov chains with an infinite state space. However, this article concentrates on the discrete-time...

additive Markov chain is a Markov chain with an additive conditional probability function. Here the process is a discrete-time Markov chain of order m...

Discrete-time Markov chain § Stationary distributions and continuous-time Markov chain § Stationary distribution, a special distribution for a Markov...

Ising model. A discrete-time stochastic process satisfying the Markov property is known as a Markov chain. A stochastic process has the Markov property if...

examples of Markov chains and Markov processes in action. All examples are in the countable state space. For an overview of Markov chains in general state...

be discrete-time stochastic processes and n ≥ 1 {\displaystyle n\geq 1} . The pair ( X n , Y n ) {\displaystyle (X_{n},Y_{n})} is a hidden Markov model...

equation. The Leslie model is very similar to a discrete-time Markov chain. The main difference is that in a Markov model, one would have f x + s x = 1 {\displaystyle...

from its connection to Markov chains, a concept developed by the Russian mathematician Andrey Markov. The "Markov" in "Markov decision process" refers...

and congestion collapse. To understand stability, Lam created a discrete-time Markov chain model for analyzing the statistical behaviour of slotted ALOHA...

and sufficient condition for a Markov chain or continuous-time Markov chain to be stochastically identical to its time-reversed version. The theorem states...

Markov chain on a measurable state space is a discrete-time-homogeneous Markov chain with a measurable space as state space. The definition of Markov...

theory Petri net theory Discrete event system specification Boolean differential calculus Markov chain Queueing theory Discrete-event simulation Concurrent...

from discretizing the time-series to hidden Markov-models combined with wavelets and the Markov-chain mixture distribution model (MCM). Markov chain Monte...

finite state continuous-time Markov chains, by approximating the process by a discrete-time Markov chain. The original chain is scaled by the fastest...

definition of a Markov chain varies. For example, it is common to define a Markov chain as a Markov process in either discrete or continuous time with a countable...

is a discrete phase-type distribution if it is the distribution of the first passage time to the absorbing state of a terminating Markov chain with finitely...

state while starting from it within a finite time interval. Consider an irreducible discrete-time Markov chain on a countable state space S {\displaystyle...

pair of states i {\displaystyle i} and j {\displaystyle j} . A discrete time Markov chain (DTMC) with transition matrix P {\displaystyle P} and equilibrium...

of discrete time Markov processes, which are described by the Chapman–Kolmogorov equation, and sought to derive a theory of continuous time Markov processes...

including discrete-time Markov chains, continuous-time Markov chains, Markov decision processes and probabilistic extensions of the timed automata formalism...

statistics and statistical physics, the Metropolis–Hastings algorithm is a Markov chain Monte Carlo (MCMC) method for obtaining a sequence of random samples...

the probability distribution on the state space of a Markov chain is discrete and the Markov chain is homogeneous, the Chapman–Kolmogorov equations can...

) {\displaystyle (X,k)} , we can then construct a reversible discrete-time Markov chain on X {\displaystyle X} (a process known as the normalized graph...

any finite time interval. When M {\displaystyle M} has a discrete distribution, the Markov state vector M t {\displaystyle M_{t}} takes finitely many...