## Abstract In this paper we deal with the prediction theory of longβmemory time series. The purpose is to derive a general theory of the convergence of moments of the nonlinear least squares estimator so as to evaluate the asymptotic prediction mean squared error (PMSE). The asymptotic PMSE of two
Log-periodogram estimation of the memory parameter of a long-memory process under trend
β Scribed by Philipp Sibbertsen
- Publisher
- Elsevier Science
- Year
- 2003
- Tongue
- English
- Weight
- 103 KB
- Volume
- 61
- Category
- Article
- ISSN
- 0167-7152
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β¦ Synopsis
We show that log-periodogram-based estimators for the memory parameter in a stationary invertible longmemory process do not confuse small trends with long-range dependence. In the case of slowly decaying trends we show by Monte Carlo methods that the tapered periodogram is quite robust against these trends and reduces the bias obtained when employing the standard log-periodogram estimator. Thus, comparing the tapered and the non-tapered estimator gives a tool at hand for distinguishing slowly decaying trends and long-range dependence.
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