This is a preview. Log in through your library . Abstract This paper develops, for a Markov chain $\{X_n\}$ on a general space $(\mathscr{X}, \mathscr{F})$ with $n ...

With any Harris-recurrent Markov chain one can associate a sequence of random times at which the chain has the same distribution, and the chain can thereby be shown to be equivalent to one having a ...

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 ...

Brief review of conditional probability and expectation followed by a study of Markov chains, both discrete and continuous time. Queuing theory, terminology, and single queue systems are studied with ...

Markov chains provide a fundamental framework for modelling stochastic processes, where the next state depends solely on the current state. Hidden Markov models (HMMs) extend this framework by ...

In this episode probability mathematics and chess collide. In this episode probability mathematics and chess collide. What is the average number of steps it would take before a randomly moving knight ...

In 1987, Mark Jerrum (Queen Mary) and Alistair Sinclair (Berkley), both then at the University of Edinburgh, submitted a paper to the 13th Workshop on Graph-theoretic Concepts in Computer Science (WG) ...