Empirical Spectral Processes and Nonparametric Maximum Likelihood Estimation for Time Series

Rainer Dahlhaus () and Wolfgang Polonik ()
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Rainer Dahlhaus: Universität Heidelberg, Institut für Angewandte Mathematik
Wolfgang Polonik: University of California, Davis, Department of Statistics

A chapter in Empirical Process Techniques for Dependent Data, 2002, pp 275-298 from Springer

Abstract: Abstract We survey recent developments in the theory of empirical spectral processes indexed by functions and their applications to nonparametric maximum Whittle likelihood estimation for times series. The exposition covers stationary and nonstationary time series as well as Gaussian and non-Gaussian cases. Previously unpublished results are added in order to complete the overall picture.

Keywords: Spectral Density; Gaussian Process; Time Series Analysis; Empirical Process; Stationary Time Series (search for similar items in EconPapers)
Date: 2002
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4612-0099-4_10

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DOI: 10.1007/978-1-4612-0099-4_10

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