Empirical Process Techniques for Dependent Data

Edited by Herold Dehling, Thomas Mikosch and Michael Sørensen

in Springer Books from Springer

Date: 2002
ISBN: 978-1-4612-0099-4
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Chapters in this book:

Empirical Process Techniques for Dependent Data

Herold Dehling and Walter Philipp

Weak Dependence: Models and Applications

Patrick Ango Nze and Paul Doukhan

Maximal Inequalities and Empirical Central Limit Theorems

Jérôme Dedecker and Sana Louhichi

On Hoeffding’s Inequality for Dependent Random Variables

Sara A. van de Geer

On the Coupling of Dependent Random Variables and Applications

Florence Merlevède and Magda Peligrad

Empirical Processes of Residuals

István Berkes and Lajos Horvath

Asymptotic Expansion of the Empirical Process of Long Memory Moving Averages

Hira L. Koul and Donatas Surgailis

The Reduction Principle for the Empirical Process of a Long Memory Linear Process

Liudas Giraitis and Donatas Surgailis

Distributional Limit Theorems for Empirical Processes Generated by Functions of a Stationary Gaussian Process

Miguel A. Arcones

Empirical Spectral Processes and Nonparametric Maximum Likelihood Estimation for Time Series

Rainer Dahlhaus and Wolfgang Polonik

Empirical Processes Techniques for the Spectral Estimation of Fractional Processes

Philippe Soulier

Tail Empirical Processes Under Mixing Conditions

Holger Drees

On the Bootstrap and Empirical Processes for Dependent Sequences

Dragan Radulović

Frequency Domain Bootstrap for Time Series

Efstathios Paparoditis

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DOI: 10.1007/978-1-4612-0099-4

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