What is Markov chain central limit theorem?

In probability theory, the central limit theorem states that, in many situations, when independent random variables are added, their properly normalized sum tends toward a normal distribution. This article gives...

A Markov chain on a measurable state space is a discrete-time-homogeneous Markov chain with a measurable space as state space.

This article contains 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 space,...

In numerical methods for stochastic differential equations, the Markov chain approximation method belongs to the several numerical approaches used in stochastic control theory. Regrettably the simple adaptation of the deterministic...

In mathematics, a Markov information source, or simply, a Markov source, is an information source whose underlying dynamics are given by a stationary finite Markov chain.

In mathematics, the quantum Markov chain is a reformulation of the ideas of a classical Markov chain, replacing the classical definitions of probability with quantum probability.

In probability and statistics, a Markov renewal process is a random process that generalizes the notion of Markov jump processes. Other random processes like Markov chains, Poisson processes and renewal...

In probability theory, a Markov kernel is a map that in the general theory of Markov processes plays the role that the transition matrix does in the theory of Markov...

In the mathematical theory of probability, an absorbing Markov chain is a Markov chain in which every state can reach an absorbing state. An absorbing state is a state that,...

In probability theory, an 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 and the...