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On the Optimal Segment Length for Parameter Estimates for Locally Stationary Time Series |
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| Authors: | Rainer Dahlhaus,& Liudas Giraitis |
| Affiliation: | Universitat Heidelberg |
| Abstract: | We discuss the behaviour of parameter estimates when stationary time series models are fitted locally to non-stationary processes which have an evolutionary spectral representation. A particular example is the estimation for an autoregressive process with time-varying coefficients by local Yule–Walker estimates. The bias and the mean squared error for the parameter estimates are calculated and the optimal length of the data segment is determined. |
| Keywords: | Non-stationary processes autoregressive processes evolutionary spectrum local time series models time-varying parameters segment length |