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Functional Gaussian approximation for dependent structures

Author: Florence Merlevède; Magda Peligrad; Sergey Utev
Publisher: Oxford : Oxford University Press, 2019.
Series: Oxford studies in probability, 6.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:

This book has its origin in the need of developing and analysing mathematical models for phenomena that evolve in time and influence each another, and aims at a better understanding of the structure  Read more...

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Document Type: Book
All Authors / Contributors: Florence Merlevède; Magda Peligrad; Sergey Utev
ISBN: 9780198826941 019882694X
OCLC Number: 1084396275
Notes: Formerly CIP.
Description: xv, 478 pages ; 24 cm.
Contents: 1: Introduction to Stochastic Processes2: Moment Inequalities and Gaussian Approximation for Martingales3: Moment Inequalities via Martingale Methods4: Gaussian Approximation via Martingale Methods5: Dependence coefficients for sequences6: Moment Inequalities and Gaussian Approximation for Mixing Sequences7: Weakly associated random variables : L2-bounds and approximation by independent structures8: Maximal moment inequalities for weakly negatively dependent variables9: Gaussian approximation under asymptotic negative dependence10: Examples of Stationary Sequences with Approximate Negative Dependence11: Stationary Sequences in a Random Time Scenery12: Linear Processes13: Random walk in random scenery14: Reversible Markov chains15: Functional central limit theorem for empirical processes16: Application to the uniform laws of large numbers for dependent processes17: Examples and Counterexamples
Series Title: Oxford studies in probability, 6.
Responsibility: Florence Merlevède, Université Paris-Est, Magda Peligrad, University of Cincinnati, Sergey Utev, University of Leicester.

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