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:
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.