Lecture

Invariant Distributions: Markov Chains

In course

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Description

This lecture covers the concept of invariant distributions in Markov chains, discussing recurrent and transient states, the strong Markov property, and the asymptotic behavior of Markov chains. It also explores the conditions for a chain to approach equilibrium and the importance of periodicity and aperiodicity in determining convergence. The lecture concludes with practical applications such as PageRank in Google's ranking algorithm.

Official source

https://mediaspace.epfl.ch/media/0_dwpmgpwp

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Ontological neighbourhood

Statistics

Statistical inference: Mathematical statistics

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