Title
Maxima in hypercubes
Abstract
We derive a Berry-Esseen bound, essentially of the order of the square of the standard deviation, for the number of maxima in random samples from (0, 1)d. The bound is, although not optimal, the first of its kind for the number of maxima in dimensions higher than two. The proof uses Poisson processes and Stein's method. We also propose a new method for computing the variance and derive an asymptotic expansion. The methods of proof we propose are of some generality and applicable to other regions such as d-dimensional simplex.
Year
DOI
Venue
2005
10.1002/rsa.20053
Random Struct. Algorithms
Keywords
Field
DocType
random sample,asymptotic expansion,d-dimensional simplex,standard deviation,poisson process,new method,random sampling,stein s method
Discrete mathematics,Combinatorics,Simplex,Asymptotic expansion,Poisson distribution,Standard deviation,Maxima,Hypercube,Generality,Mathematics
Journal
Volume
Issue
ISSN
27
3
1042-9832
Citations 
PageRank 
References 
9
1.14
12
Authors
4
Name
Order
Citations
PageRank
Zhi-Dong Bai18529.46
Luc Devroye2819214.10
Hsien-Kuei Hwang336538.02
Tsung-Hsi Tsai4818.20