Logo

Reversible Markov Chains and Random Walks on Graphs

Reversible Markov Chains and Random Walks on Graphs
by

Publisher: University of California, Berkeley
Number of pages: 516

Description:
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; Advanced L2 Techniques for Bounding Mixing Times; Some Graph Theory and Randomized Algorithms; Continuous State, Infinite State and Random Environment; Interacting Particles on Finite Graphs; Markov Chain Monte Carlo.

Home page url

Download or read it online for free here:
Download link
(1.8MB, PDF)

Similar books

Book cover: Topics in Random Matrix TheoryTopics in Random Matrix Theory
by
This is a textbook for a graduate course on random matrix theory, inspired by recent developments in the subject. This text focuses on foundational topics in random matrix theory upon which the most recent work has been based.
(14408 views)
Book cover: Convergence of Stochastic ProcessesConvergence of Stochastic Processes
by - Springer
Selected parts of empirical process theory, with applications to mathematical statistics. The book describes the combinatorial ideas needed to prove maximal inequalities for empirical processes indexed by classes of sets or classes of functions.
(16071 views)
Book cover: Applied Nonparametric RegressionApplied Nonparametric Regression
by - Cambridge University Press
Nonparametric regression analysis has become central to economic theory. Hardle, by writing the first comprehensive and accessible book on the subject, contributed enormously to making nonparametric regression equally central to econometric practice.
(27004 views)
Book cover: Probability, Statistics and Stochastic ProcessesProbability, Statistics and Stochastic Processes
by
Contents: Probability (Probability Calculus, Random Variables, Discrete and Continuous Distributions); Statistics (Handling of Data, Sampling, Estimation, Hypothesis Testing); Stochastic Processes (Markov Processes, Continuous-Time Processes).
(12178 views)