**Reversible Markov Chains and Random Walks on Graphs**

by David Aldous, James Allen Fill

**Publisher**: University of California, Berkeley 2014**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.

Download or read it online for free here:

**Download link**

(1.8MB, PDF)

## Similar books

**A Minimum of Stochastics for Scientists**

by

**Noel Corngold**-

**Caltech**

The book introduces students to the ideas and attitudes that underlie the statistical modeling of physical, chemical, biological systems. The text contains material the author have tried to convey to an audience composed mostly of graduate students.

(

**8301**views)

**Markov Chains and Stochastic Stability**

by

**S.P. Meyn, R.L. Tweedie**-

**Springer**

The book on the theory of general state space Markov chains, and its application to time series analysis, operations research and systems and control theory. An advanced graduate text and a monograph treating the stability of Markov chains.

(

**16819**views)

**A defense of Columbo: A multilevel introduction to probabilistic reasoning**

by

**G. D'Agostini**-

**arXiv**

Triggered by a recent interesting article on the too frequent incorrect use of probabilistic evidence in courts, the author introduces the basic concepts of probabilistic inference with a toy model, and discusses several important issues.

(

**11607**views)

**Random Matrix Models and Their Applications**

by

**Pavel Bleher, Alexander Its**-

**Cambridge University Press**

The book covers broad areas such as topologic and combinatorial aspects of random matrix theory; scaling limits, universalities and phase transitions in matrix models; universalities for random polynomials; and applications to integrable systems.

(

**11895**views)