Lecture

Stationary Distribution in Markov Chains

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In course

COM-516: Markov chains and algorithmic applications

The study of random walks finds many applications in computer science and communications. The goal of the course is to get familiar with the theory of random walks, and to get an overview of some applications of this theory to problems of interest in commu ...

Description

This lecture covers the concept of stationary distribution in Markov chains, defining it as the distribution at time n, and explaining its existence and properties. The instructor discusses the implications of a stationary distribution, such as the equality T.P = T.P and the conditions for positive-recurrence. Mathematical remarks are made regarding column vectors and stochastic matrices, leading to theorems and corollaries about the positive-recurrence of Markov chains and the existence of unique stationary distributions. The lecture concludes with practical remarks on the uniqueness and existence of stationary distributions in Markov chains.

Official source

Ontological neighbourhood

Mathematics

Algebra: Linear algebra

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