Description: Functional Gaussian Approximation for Dependent Structures, Hardcover by Merlevede, Florence; Peligrad, Magda; Utev, Sergey, ISBN 019882694X, ISBN-13 9780198826941, Like New Used, Free shipping in the US Functional Gaussian Approximation for Dependent Structures develops and analyses mathematical models for phenomena that evolve in time and influence each another. It provides a better understanding of the structure and asymptotic behaviour of stochastic processes.
Two approaches are taken. Firstly, the authors present tools for dealing with the dependent structures used to obtain normal approximations. Secondly, they apply normal approximations to various examples. The main tools consist of inequalities for dependent sequences of random variables, leading to
limit theorems, including the functional central limit theorem and functional moderate deviation principle. The results point out large classes of dependent random variables which satisfy invariance principles, making possible the statistical study of data coming from stochastic processes both with
short and long memory.
The dependence structures considered throughout th include the traditional mixing structures, martingale-like structures, and weakly negatively dependent structures, which link the notion of mixing to the notions of association and negative dependence. Several applications are carefully
selected to exhibit the importance of the theoretical results. They include random walks in random scenery and determinantal processes. In addition, due to their importance in analysing new data in economics, linear processes with dependent innovations will also be considered and analysed.
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Book Title: Functional Gaussian Approximation for Dependent Structures
Number of Pages: 496 Pages
Language: English
Publication Name: Functional Gaussian Approximation for Dependent Structures
Publisher: Oxford University Press, Incorporated
Subject: Functional Analysis, Probability & Statistics / Stochastic Processes, Probability & Statistics / General, General
Item Height: 1.1 in
Publication Year: 2019
Item Weight: 33.2 Oz
Type: Textbook
Author: Magda Peligrad, Florence Merlevede, Sergey Utev
Subject Area: Mathematics
Item Length: 9.3 in
Item Width: 6.5 in
Format: Hardcover
