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Introduction to mixing times
The mixing time of a Markov chain is a parameter that describes the time required for the distance to stationarity to be small. The idea of the talk will be to introduce the concept of a mixing time and give bounds for some examples that are indicative of some standard techniques. In particular we will show that the spectral gap characterises the mixing time for irreducible and reversible continuous time Markov processes with finite state spaces. Some relevant references are:
Markov Chains and Mixing Times by Levin, Peres and Wilmer,
Lectures on Finite Markov Chains by Saloff-Coste.
Date:
14 February 2019, 12:00
Venue:
24-29 St Giles', 24-29 St Giles' OX1 3LB
Venue Details:
Small Lecture Theatre, Department of Statistics
Speaker:
James Ayre (University of Oxford)
Organising department:
Mathematical Institute
Organiser contact email address:
aaron.smith@magd.ox.ac.uk
Part of:
Junior Probability Seminar
Booking required?:
Not required
Audience:
Public
Editor:
Aaron Smith
