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Fitting Time Series Models to Nonstationary Processes

Dahlhaus, Rainer

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Abstract

A general minimum distance estimation procedure is presented fornonstationary time series models that have an evolutionary spectralrepresentation. The asymptotic properties of the estimate is derived underthe assumption of possible model misspecification. For autoregressiveprocesses with time varying coefficients the estimate is compared to theleast squares estimate. Furthermore, the behaviour of estimates isexplained when a stationary model is fitted to a nonstationary process.

Item Type: Working paper
Place of Publication: Heidelberg
Date Deposited: 20 Jun 2016 09:26
Date: 1997
Number of Pages: 43
Faculties / Institutes: The Faculty of Mathematics and Computer Science > Department of Applied Mathematics
Subjects: 510 Mathematics
Uncontrolled Keywords: Nonstationary processes; time series; evolutionary spectra; minimum distance estimates; model selection
Schriftenreihe ID: Beiträge zur Statistik > Beiträge
Additional Information: auch erschienen in: The Annals of Statistics (1997), Vol. 25, No. I, 1-37
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