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Stochastic Inequalities and Applications (Progress in Probability)
 
 

Stochastic Inequalities and Applications (Progress in Probability) (Hardcover)

by Evariste Gine (Editor), Christian Houdre (Editor), D. Nualart (Editor) "Let K be a convex body in Rn with the properties: 1) voln(K) = 1, where voln stands for the Lebesgue measure; 2) given x..." (more)
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Synopsis
Concentration inequalities, which express the fact that certain complicated random variables are almost constant, have proven of utmost importance in many areas of probability and statistics. This volume contains refined versions of these inequalities, and their relationship to many applications particularly in stochastic analysis. The broad range and the high quality of the contributions make this book highly attractive for graduates, postgraduates and researchers in the above areas.

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First Sentence
Let K be a convex body in Rn with the properties: 1) voln(K) = 1, where voln stands for the Lebesgue measure; 2) given x K, y Rn such that |yj| |xj|, for all j n, we have y K; 3) the integrals Kx2j dx = L2K do not depend on j n. Read the first page
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