Publikation: Recent Developments in Location Estimation and Regression for Long-Memory Processes
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The problem of long-range dependence in statistical applications has been known to scientists and applied statisticians long before suitable models were known. Parsimonious models with such behaviour are stationary processes with non-summable correlations. Many classical limit theorems do not hold for these processes and rates of convergence are slower than under independence or weak dependence. Therefore, for many statistics, usual confidence intervals are too small by a factor which tends to infinity with increasing sample size. In this paper we give a survey of recent results on point and interval estimation of location and of the coefficients in parametric linear regression, as well as nonparametric regression.
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BERAN, Jan, 1993. Recent Developments in Location Estimation and Regression for Long-Memory Processes. In: BRILLINGER, David, ed., Peter CAINES, ed., John GEWEKE, ed., Emanuel PARZEN, ed., Murray ROSENBLATT, ed., Murad S. TAQQU, ed.. New Directions in Time Series Analysis. New York, NY: Springer New York, 1993, pp. 1-9. The IMA Volumes in Mathematics and its Applications. 46. ISBN 978-1-4613-9298-9. Available under: doi: 10.1007/978-1-4613-9296-5_1BibTex
@incollection{Beran1993Recen-27587, year={1993}, doi={10.1007/978-1-4613-9296-5_1}, title={Recent Developments in Location Estimation and Regression for Long-Memory Processes}, number={46}, isbn={978-1-4613-9298-9}, publisher={Springer New York}, address={New York, NY}, series={The IMA Volumes in Mathematics and its Applications}, booktitle={New Directions in Time Series Analysis}, pages={1--9}, editor={Brillinger, David and Caines, Peter and Geweke, John and Parzen, Emanuel and Rosenblatt, Murray and Taqqu, Murad S.}, author={Beran, Jan} }
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