Stochastic Inequalities and ApplicationsEvariste Giné, Christian Houdré, David Nualart Springer Science & Business Media, 24 oct 2003 - 367 páginas 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. |
Índice
III | 3 |
VII | 15 |
VIII | 23 |
IX | 33 |
X | 53 |
XI | 55 |
XII | 71 |
XIV | 77 |
XXI | 169 |
XXII | 187 |
XXIII | 189 |
XXIV | 213 |
XXV | 249 |
XXVI | 279 |
XXVII | 299 |
XXVIII | 301 |
Otras ediciones - Ver todo
Stochastic Inequalities and Applications Evariste Giné,Christian Houdré,David Nualart Vista previa restringida - 2012 |
Stochastic Inequalities and Applications Evariste Gine,Christian Houdre,David Nualart No hay ninguna vista previa disponible - 2003 |
Stochastic Inequalities and Applications Evariste Giné,Christian Houdré,David Nualart No hay ninguna vista previa disponible - 2012 |
Términos y frases comunes
apply assume assumption asymptotic Banach space Bernoulli Brownian motion coefficients concentration inequalities consider convergence convex function Corollary covariance defined denote density distribution E-mail address e¹² empirical processes entropy estimate exists finite follows function f Gaussian Hence implies independent random variables infimum integral Khinchine inequality kn/n large numbers Ledoux Lemma Lévy process lim sup limit theorems linear log log Malliavin Calculus martingale Math Mathematics measurable function non-negative norm notation Note obtain positive constant probability measure probability space proof of Theorem Proposition prove queue rate function real numbers respect result satisfies the LDP sequence Sobolev inequalities solution spectral gap splitting-up stochastic differential equations sub-additive sup sup symmetric Talagrand Theorem 2.1 variance vectors Wiener process zero
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