Markov Chains and Mixing Times
by D. A. Levin, Y. Peres, E. L. Wilmer
Publisher: American Mathematical Society 2008
ISBN/ASIN: 0821847392
ISBN-13: 9780821847398
Number of pages: 387
Description:
This book is an introduction to the modern approach to the theory of Markov chains. The main goal of this approach is to determine the rate of convergence of a Markov chain to the stationary distribution as a function of the size and geometry of the state space. The authors develop the key tools for estimating convergence times, including coupling, strong stationary times, and spectral methods.
Download or read it online for free here:
Download link
(4.5MB, PDF)
Similar books
An Introduction to Stochastic PDEsby Martin Hairer - arXiv
This text is an attempt to give a reasonably self-contained presentation of the basic theory of stochastic partial differential equations, taking for granted basic measure theory, functional analysis and probability theory, but nothing else.
(14295 views)
Seeing Theory: A visual introduction to probability and statisticsby T. Devlin, J. Guo, D. Kunin, D. Xiang - Brown University
The intent of the website and these notes is to provide an intuitive supplement to an introductory level probability and statistics course. The level is also aimed at students who are returning to the subject and would like a concise refresher ...
(9145 views)
Design of Comparative Experimentsby R. A. Bailey - Cambridge University Press
This book develops a coherent framework for thinking about factors that affect experiments and their relationships, including the use of Hasse diagrams. The book is ideal for advanced undergraduate and beginning graduate courses.
(23807 views)
Reversible Markov Chains and Random Walks on Graphsby David Aldous, James Allen Fill - University of California, Berkeley
From the table of contents: General Markov Chains; Reversible Markov Chains; Hitting and Convergence Time, and Flow Rate, Parameters for Reversible Markov Chains; Special Graphs and Trees; Cover Times; Symmetric Graphs and Chains; etc.
(15066 views)