
Probability Approximations via the Poisson Clumping Heuristic
David Aldous(Author)
Springer (Publisher)
Published on 14. November 1988
Book
Hardback
XVI, 272 pages
978-0-387-96899-5 (ISBN)
Description
If you place a large number of points randomly in the unit square, what is the distribution of the radius of the largest circle containing no points? Of the smallest circle containing 4 points? Why do Brownian sample paths have local maxima but not points of increase, and how nearly do they have points of increase? Given two long strings of letters drawn i. i. d. from a finite alphabet, how long is the longest consecutive (resp. non-consecutive) substring appearing in both strings? If an imaginary particle performs a simple random walk on the vertices of a high-dimensional cube, how long does it take to visit every vertex? If a particle moves under the influence of a potential field and random perturbations of velocity, how long does it take to escape from a deep potential well? If cars on a freeway move with constant speed (random from car to car), what is the longest stretch of empty road you will see during a long journey? If you take a large i. i. d. sample from a 2-dimensional rotationally-invariant distribution, what is the maximum over all half-spaces of the deviation between the empirical and true distributions? These questions cover a wide cross-section of theoretical and applied probability. The common theme is that they all deal with maxima or min ima, in some sense.
More details
Series
Edition
1989 ed.
Language
English
Place of publication
New York
United States
Target group
Professional and scholarly
Research
Product notice
sewn/stitched
Cloth over boards
Illustrations
XVI, 272 p.
Dimensions
Height: 241 mm
Width: 163 mm
Thickness: 25 mm
Weight
579 gr
ISBN-13
978-0-387-96899-5 (9780387968995)
DOI
10.1007/978-1-4757-6283-9
Schweitzer Classification
Other editions
Additional editions

Book
12/2010
Springer
€128.39
Shipment within 15-20 days
Content
A The Heuristic.- B Markov Chain Hitting Times.- C Extremes of Stationary Processes.- D Extremes of Locally Brownian Processes.- E Simple Combinatorics.- F Combinatorics for Processes.- G Exponential Combinatorial Extrema.- H Stochastic Geometry.- I Multi-Dimensional Diffusions.- J Random Fields.- K Brownian Motion: Local Distributions.- L Miscellaneous Examples.- M The Eigenvalue Method.- Postscript.