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Uniform Central Limit Theorems
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This book shows how the central limit theorem for independent, identically distributed random variables with values in general, multidimensional spaces, holds uniformly over some large classes of functions. The author, an acknowledged expert, gives a thorough treatment of the subject, including several topics not found in any previous book, such as the Fernique-Talagrand majorizing measure theorem for Gaussian processes, an extended treatment of Vapnik-Chervonenkis combinatorics, the Ossiander L2 bracketing central limit theorem, the Giné-Zinn bootstrap central limit theorem in probability, the Bronstein theorem on approximation of convex sets, and the Shor theorem on rates of convergence over lower layers. Other results of Talagrand and others are surveyed without proofs in separate sections. Problems are included at the end of each chapter so the book can be used as an advanced text. The book will interest mathematicians working in probability, mathematical statisticians and computer scientists working in computer learning theory.
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Cambridge University Press; July 1999
452 pages; ISBN 9780511885174
Read online, or download in secure PDF format
452 pages; ISBN 9780511885174
Read online, or download in secure PDF format
Subject categories
- Academic > Mathematics > Probabilities. Mathematical statistics > Probabilities
- Academic > Mathematics > Probabilities. Mathematical statistics > Distribution (Probability theory)
- Academic > Mathematics > Probabilities. Mathematical statistics > Large deviations
- Academic > Mathematics > General
- Mathematics > Probability & Statistics
- Medicine
ISBNs
0511885172
9780511885174
9780521461023