Weak Convergence of Stochastic Processes : With Applications to Statistical Limit Theorems.

Weak Convergence of Stochastic Processes : With Applications to Statistical Limit Theorems.

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Bibliographic Details
Author / Creator:	Mandrekar, Vidyadhar S.
Imprint:	Berlin/Boston, GERMANY : De Gruyter, 2016.
Description:	1 online resource (148)
Language:	English
Series:	De Gruyter Textbook ; 64
Subject:	Limit theorems (Probability theory) Fourier transformations. Stochastic processes. Fourier transformations. Limit theorems (Probability theory) Stochastic processes. Electronic books.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/11757520

Hidden Bibliographic Details
ISBN:	3110476312 9783110476316 9783110475456 3110475456 3110475421
Notes:	Print version record.
Summary:	The purpose of this book is to present results on the subject of weak convergence in function spaces to study invariance principles in statistical applications to dependent random variables, U-statistics, censor data analysis. Different techniques, formerly available only in a broad range of literature, are for the first time presented here in a self-contained fashion. Contents:Weak convergence of stochastic processesWeak convergence in metric spacesWeak convergence on C[0, 1] and D[0,∞)Central limit theorem for semi-martingales and applicationsCentral limit theorems for dependent random variablesEmpirical processBibliography.

Table of Contents:

1. Weak convergence of stochastic processes ; 2. Weak convergence in metric spaces ; 3. Weak convergence on C[0, 1] and D[0,8) ; 4. Central limit theorem for semi-martingales and applications ; 5. Central limit theorems for dependent random variables ; 6. Empirical process.