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 ...

High-order Markov chain models extend the conventional framework by incorporating dependencies that span several previous states rather than solely the immediate past. This extension allows for a ...

A Markov Chain is a sequence of random values whose probabilities at a time interval depends upon the value of the number at the previous time. A Markov Chain is a sequence of random values whose ...

Journal of Applied Probability, Vol. 36, No. 1 (Mar., 1999), pp. 78-85 (8 pages) This paper is concerned with submultiplicative moments for the stationary distributions π of some Markov chains taking ...

This course is compulsory on the MSc in Operations Research & Analytics. This course is not available as an outside option to students on other programmes. The course covers theory including the ...

In this paper we prove an upper large deviation bound for a general class of Markov processes, which includes processes with discontinuous statistics. We also specialize the results to a class of jump ...

Mathematics often seems like an abstract concept, but its applications can have profound impacts on the world around us. From predicting the next word in a sentence to understanding how Google’s ...