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Author: Ivan Nourdin Publisher: Cambridge University Press ISBN: 1107017777 Category : Mathematics Languages : en Pages : 255
Book Description
This book shows how quantitative central limit theorems can be deduced by combining two powerful probabilistic techniques: Stein's method and Malliavin calculus.
Author: Ivan Nourdin Publisher: Cambridge University Press ISBN: 1107017777 Category : Mathematics Languages : en Pages : 255
Book Description
This book shows how quantitative central limit theorems can be deduced by combining two powerful probabilistic techniques: Stein's method and Malliavin calculus.
Author: Ivan Nourdin Publisher: ISBN: 9781139380218 Category : MATHEMATICS Languages : en Pages : 256
Book Description
"This is a text about probabilistic approximations, which are mathematical statements providing estimates of the distance between the laws of two random objects. As the title suggests, we will be mainly interested in approximations involving one or more normal (equivalently called Gaussian) random elements. Normal approximations are naturally connected with central limit theorems (CLTs), i.e. convergence results displaying a Gaussian limit, and are one of the leading themes of the whole theory of probability"--
Author: David Nualart Publisher: Cambridge University Press ISBN: 1107039126 Category : Business & Economics Languages : en Pages : 249
Book Description
A compact introduction to this active and powerful area of research, combining basic theory, core techniques, and recent applications.
Author: Louis H.Y. Chen Publisher: Springer Science & Business Media ISBN: 3642150071 Category : Mathematics Languages : en Pages : 411
Book Description
Since its introduction in 1972, Stein’s method has offered a completely novel way of evaluating the quality of normal approximations. Through its characterizing equation approach, it is able to provide approximation error bounds in a wide variety of situations, even in the presence of complicated dependence. Use of the method thus opens the door to the analysis of random phenomena arising in areas including statistics, physics, and molecular biology. Though Stein's method for normal approximation is now mature, the literature has so far lacked a complete self contained treatment. This volume contains thorough coverage of the method’s fundamentals, includes a large number of recent developments in both theory and applications, and will help accelerate the appreciation, understanding, and use of Stein's method by providing the reader with the tools needed to apply it in new situations. It addresses researchers as well as graduate students in Probability, Statistics and Combinatorics.
Author: Ivan Nourdin Publisher: Springer Science & Business Media ISBN: 884702823X Category : Mathematics Languages : en Pages : 133
Book Description
Fractional Brownian motion (fBm) is a stochastic process which deviates significantly from Brownian motion and semimartingales, and others classically used in probability theory. As a centered Gaussian process, it is characterized by the stationarity of its increments and a medium- or long-memory property which is in sharp contrast with martingales and Markov processes. FBm has become a popular choice for applications where classical processes cannot model these non-trivial properties; for instance long memory, which is also known as persistence, is of fundamental importance for financial data and in internet traffic. The mathematical theory of fBm is currently being developed vigorously by a number of stochastic analysts, in various directions, using complementary and sometimes competing tools. This book is concerned with several aspects of fBm, including the stochastic integration with respect to it, the study of its supremum and its appearance as limit of partial sums involving stationary sequences, to name but a few. The book is addressed to researchers and graduate students in probability and mathematical statistics. With very few exceptions (where precise references are given), every stated result is proved.
Author: Hiroyuki Matsumoto Publisher: Cambridge University Press ISBN: 110714051X Category : Mathematics Languages : en Pages : 359
Book Description
Developing the Itô calculus and Malliavin calculus in tandem, this book crystallizes modern day stochastic analysis into a single volume.
Author: Vladimir Igorevich Bogachev Publisher: American Mathematical Soc. ISBN: 082184993X Category : Mathematics Languages : en Pages : 506
Book Description
This book provides the reader with the principal concepts and results related to differential properties of measures on infinite dimensional spaces. In the finite dimensional case such properties are described in terms of densities of measures with respect to Lebesgue measure. In the infinite dimensional case new phenomena arise. For the first time a detailed account is given of the theory of differentiable measures, initiated by S. V. Fomin in the 1960s; since then the method has found many various important applications. Differentiable properties are described for diverse concrete classes of measures arising in applications, for example, Gaussian, convex, stable, Gibbsian, and for distributions of random processes. Sobolev classes for measures on finite and infinite dimensional spaces are discussed in detail. Finally, we present the main ideas and results of the Malliavin calculus--a powerful method to study smoothness properties of the distributions of nonlinear functionals on infinite dimensional spaces with measures. The target readership includes mathematicians and physicists whose research is related to measures on infinite dimensional spaces, distributions of random processes, and differential equations in infinite dimensional spaces. The book includes an extensive bibliography on the subject.
Author: Horst Osswald Publisher: Cambridge University Press ISBN: 1107016142 Category : Mathematics Languages : en Pages : 429
Book Description
After functional, measure and stochastic analysis prerequisites, the author covers chaos decomposition, Skorohod integral processes, Malliavin derivative and Girsanov transformations.
Author: David Applebaum Publisher: Cambridge University Press ISBN: 1139477986 Category : Mathematics Languages : en Pages : 461
Book Description
Lévy processes form a wide and rich class of random process, and have many applications ranging from physics to finance. Stochastic calculus is the mathematics of systems interacting with random noise. Here, the author ties these two subjects together, beginning with an introduction to the general theory of Lévy processes, then leading on to develop the stochastic calculus for Lévy processes in a direct and accessible way. This fully revised edition now features a number of new topics. These include: regular variation and subexponential distributions; necessary and sufficient conditions for Lévy processes to have finite moments; characterisation of Lévy processes with finite variation; Kunita's estimates for moments of Lévy type stochastic integrals; new proofs of Ito representation and martingale representation theorems for general Lévy processes; multiple Wiener-Lévy integrals and chaos decomposition; an introduction to Malliavin calculus; an introduction to stability theory for Lévy-driven SDEs.
Author: Ivan Nourdin
Author: Ivan Nourdin
Author: Ivan Nourdin
Author: David Nualart
Author: Louis H.Y. Chen
Author: Ivan Nourdin
Author: Hiroyuki Matsumoto
Author: Vladimir Igorevich Bogachev
Author: Horst Osswald
Author: Paul Malliavin
Author: David Applebaum