Abstract
An asymptotic approach for nonstationary processes which locally show a stationary behaviour is presented. Kernel methods for local estimates of the covariance structure and the time varying spectral density are discussed. In particular, we calculate the bias of the estimates due to nonstationarity and determine the optimal bandwidth. Furthermore, the relation to Priestley’s theory of processes with evolutionary spectra is discussed.
This work has been supported by the Deutsche Forschungsgemeinschaft (DA 187/9-1) and by a European Union Capital and Mobility Programme (ERB CHRX-CT 940693).
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Dahlhaus, R. (1996). Asymptotic statistical inference for nonstationary processes with evolutionary spectra. In: Robinson, P.M., Rosenblatt, M. (eds) Athens Conference on Applied Probability and Time Series Analysis. Lecture Notes in Statistics, vol 115. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2412-9_11
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DOI: https://doi.org/10.1007/978-1-4612-2412-9_11
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