Fitting time series models to nonstationary processes

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Fitting time series models to nonstationary processes

R. Dahlhaus

Source: Ann. Statist. Volume 25, Number 1 (1997), 1-37.

Abstract

A general minimum distance estimation procedure is presented for nonstationary time series models that have an evolutionary spectral representation. The asymptotic properties of the estimate are derived under the assumption of possible model misspecification. For autoregressive processes with time varying coefficients, the estimate is compared to the least squares estimate. Furthermore, the behavior of estimates is explained when a stationary model is fitted to a nonstationary process.

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Primary Subjects: 62M15

Secondary Subjects: 62F10

Keywords: Nonstationary processes; time series; evolutionary spectra; minimum distance estimates; model selection

Full-text: Open access

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Links and Identifiers

Permanent link to this document: http://projecteuclid.org/euclid.aos/1034276620
Mathematical Reviews number (MathSciNet): MR1429916
Digital Object Identifier: doi:10.1214/aos/1034276620
Zentralblatt MATH identifier: 0871.62080

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