9781107160156-1107160154-Probability on Trees and Networks (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 42)

Probability on Trees and Networks (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 42)

ISBN-13: 9781107160156
ISBN-10: 1107160154
Edition: 1
Author: Yuval Peres, Russell Lyons
Publication date: 2017
Publisher: Cambridge University Press
Format: Hardcover 720 pages
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Book details

ISBN-13: 9781107160156
ISBN-10: 1107160154
Edition: 1
Author: Yuval Peres, Russell Lyons
Publication date: 2017
Publisher: Cambridge University Press
Format: Hardcover 720 pages

Summary

Probability on Trees and Networks (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 42) (ISBN-13: 9781107160156 and ISBN-10: 1107160154), written by authors Yuval Peres, Russell Lyons, was published by Cambridge University Press in 2017. With an overall rating of 3.7 stars, it's a notable title among other Applied (Mathematics) books. You can easily purchase or rent Probability on Trees and Networks (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 42) (Hardcover, Used) from BooksRun, along with many other new and used Applied books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $13.4.

Description

Starting around the late 1950s, several research communities began relating the geometry of graphs to stochastic processes on these graphs. This book, twenty years in the making, ties together research in the field, encompassing work on percolation, isoperimetric inequalities, eigenvalues, transition probabilities, and random walks. Written by two leading researchers, the text emphasizes intuition, while giving complete proofs and more than 850 exercises. Many recent developments, in which the authors have played a leading role, are discussed, including percolation on trees and Cayley graphs, uniform spanning forests, the mass-transport technique, and connections on random walks on graphs to embedding in Hilbert space. This state-of-the-art account of probability on networks will be indispensable for graduate students and researchers alike.

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