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 ...

Advances in Applied Probability, Vol. 26, No. 4 (Dec., 1994), pp. 988-1005 (18 pages) This paper studies the absorption time of an integer-valued Markov chain with a lower-triangular transition matrix ...

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 ...

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 ...

Much work has focused on developing exact tests for the analysis of discrete data using log linear or logistic regression models. A parametric model is tested for a dataset by conditioning on the ...

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 ...