Institute of Mathematical Statistics Collections

High Dimensional Probability V: The Luminy Volume

Editor: Christian Houdré
Editor: Vladimir Koltchinskii
Editor: David M. Mason
Editor: Magda Peligrad

Collections, Volume 5
Beachwood, Ohio, USA: Institute of Mathematical Statistics, 2009.
356 pp.

Abstract:

The term High Dimensional Probability in the title of this volume refers to a circle of ideas and problems that originated in Probability in Banach Spaces and the Theory of Gaussian Processes more than forty years ago. Initially, the main focus was on the study of necessary and sufficient conditions for the continuity of Gaussian processes and of classical limit theorems–laws of large numbers, laws of iterated logarithm and central limit theorems in Banach spaces.

Gradually, it was realized that solving these problems requires taking into account some important geometric structures associated with random variables in high dimensional and infinite dimensional spaces. For instance, in the case of Gaussian processes, it was understood that a natural way to characterize the properties of their sample paths (boundedness, continuity, etc.) is to relate them to certain geometric characteristics (metric entropy, majorizing measures, generic chaining) of the parameter space equipped with the metric induced by the covariance structure of the process. Similar considerations turned out to be very useful and powerful in the study of limit theorems in Banach spaces and empirical processes. It was also understood that the crux of the problem is related to rather general probabilistic phenomena in high dimensional spaces such as, for instance, measure concentration. Parallel developments occurred in some other areas of mathematics such as convex geometry, Banach spaces, asymptotic geometric analysis, combinatorics, random matrices and stochastic processes. Moreover, the methods of high dimensional probability were found to have a number of important applications in these areas as well as in Statistics and Computer Science. This breadth is very well illustrated by the contributions present in this volume.

Most of the papers in this volume were presented at the Vth International Conference on High Dimensional Probability (HDP V) held at le Centre International de Rencontres Mathématiques, in Luminy, France on May 26-May 30, 2008. This was the fifteenth in a series of conferences that began in Strasbourg in 1973 and continued with nine conferences on Probability in Banach Spaces and five conferences on High Dimensional Probability.

The participants of this conference are grateful for the support of the C.I.R.M., N.S.F. and N.S.A. and for the publication of the proceedings of HDP V by the I.M.S.

Permanent link to this monograph: http://projecteuclid.org/euclid.imsc/1265119251
ISBN:978-0-940600-78-2

Copyright © 2009, Institute of Mathematical Statistics.

Title and Copyright Pages

i-ii

Table of Contents

iii-iv

Contributor's List

v-vi

Dedication

vii

Preface

viii

On weighted isoperimetric and Poincaré-type inequalities

Sergey G. Bobkov, and Michel Ledoux; 1-29

A note on positive definite norm dependent functions

Alexander Koldobsky; 30-36

Gaussian approximation of moments of sums of independent symmetric random variables with logarithmically concave tails

Rafał Latała; 37-42

Gaussian integrals involving absolute value functions

Wenbo V. Li, and Ang Wei; 43-59

Weak invariance principle and exponential bounds for some special functions of intermittent maps

Jérôme Dedecker, and Florence Merlevède; 60-72

Interpolation spaces and the CLT in Banach spaces

Jim Kuelbs, and Joel Zinn; 73-83

Uniform Central Limit Theorems for pregaussian classes of functions

Dragan Radulović, and Marten Wegkamp; 84-102

A note on bounds for VC dimensions

Jon A. Wellner, and Aad van der Vaart; 103-107

Limit theorems and exponential inequalities for canonical U- and V-statistics of dependent trials

Igor S. Borisov, and Nadezhda V. Volodko; 108-130

Functional Limit Laws of Strassen and Wichura type for multiple generations of branching processes

Jim Kuelbs, and Anand N. Vidyashankar; 131-152

On Stein’s method for multivariate normal approximation

Elizabeth Meckes; 153-178

A remark on the maximum eigenvalue for circulant matrices

Włodek Bryc, and Sunder Sethuraman; 179-184

On the longest increasing subsequence for finite and countable alphabets

Christian Houdré, and Trevis J. Litherland; 185-212

Some results on random circulant matrices

Mark W. Meckes; 213-223

Conditional expectations and martingales in the fractional Brownian field

Vladimir Dobrić, and Francisco M. Ojeda; 224-238

Stochastic compactness of Lévy processes

Ross Maller, and David M. Mason; 239-257

An almost sure limit theorem for Wick powers of Gaussian differences quotients

Michael B. Marcus, and Jay Rosen; 258-272

Bernstein inequality and moderate deviations under strong mixing conditions

Florence Merlevède, Magda Peligrad, and Emmanuel Rio; 273-292

Asymptotic distribution of the most powerful invariant test for invariant families

Miguel A. Arcones; 293-307

Uniform in bandwidth consistency of kernel regression estimators at a fixed point

Julia Dony, and Uwe Einmahl; 308-325

Asymptotics of statistical estimators of integral curves

Vladimir Koltchinskii, and Lyudmila Sakhanenko; 326-337

Uniform central limit theorems for sieved maximum likelihood and trigonometric series estimators on the unit circle

Richard Nickl; 338-356

Institute of Mathematical Statistics Collections

Institute of Mathematical Statistics Collections