Malliavin calculus, Stein's lemma, and densities and tails of random variables

old_uid8785
titleMalliavin calculus, Stein's lemma, and densities and tails of random variables
start_date2010/05/28
schedule11h
onlineno
summaryIvan Nourdin and Giovanni Peccati have recently established results in stochastic analysis by which, for a scalr random variable X which is differentiable in the sense of Malliavin calculus (|DX| is square-integrable), an important quantity to study is the random variableG=<DX,-DMX>, where M is the pseudo-inverse of the so-called Ornstein-Uhlenbeck semigroup generator on Wiener space. For instance G is a random way of measuring the dispersion of X since Var[X]=E[G]; plus, G is constant if and only if X is Gaussian; and comparing G to a constant can yield comparisons of X to the Gaussian law, as in limit theorems or density formulas. This presentation will review such results and the required background from Malliavin calculus, explain their relation to Stein's lemma and equation, and outline their applications to suprema of Gaussian fields, and other extensions. The results represent work in various papers by Airault, Malliavin, Nourdin, Peccati, and Viens, listed here: Airault, H.; Malliavin, P.; Viens, F. Stokes formula on the Wiener space and n-dimensional Nourdin-Peccati analysis. Journal of Functional Analysis, 258 no. 5 (2009), 1763-1783. Nourdin, I.; Peccati, G. Stein's method on Wiener chaos. Probability Theory and Related Fields, 145 (2008), no. 1, 75-118. Nourdin, I.; Viens, F. Density estimates and concentration inequalities with Malliavin calculus. Electronic Journal of Probability, 14 (2009), 2287-2309. Viens, F. Stein's lemma, Malliavin calculus, and tail bounds, with application to polymer fluctuation exponent. Stochastic Processes and their Applications 119 (2009), 3671-3698.
responsiblesCarlo, Bardet, Cottrell