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Titlebook: Cyclostationarity: Theory and Methods – IV; Contributions to the Fakher Chaari,Jacek Leskow,Anna Dudek Conference proceedings 2020 Springer

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41#
發(fā)表于 2025-3-28 15:24:43 | 只看該作者
Barbara Frank-Job,Joachim Michaelefficients vary periodically with several dominant components associated with two or more periods (for example, day and week for hourly data). In the second model, the autoregression coefficients consist of the additive periodic effects of several nominal variables (for example, the effect of hour i
42#
發(fā)表于 2025-3-28 21:45:58 | 只看該作者
Barbara Frank-Job,Joachim Michaely under a weak dependence condition. In our model that is a generalization of the work of McElroy and Politis [., .] we show that the estimator of the periodic mean function has an asymptotic distribution that depends on the degree of heavy tails and the degree of the long memory. Such an asymptotic
43#
發(fā)表于 2025-3-28 23:36:16 | 只看該作者
44#
發(fā)表于 2025-3-29 04:18:34 | 只看該作者
Psychopharmakologische BehandlungCRP) are considered. The coherent estimators are calculated by averaging of the samples taken through the non-stationary period. The component estimators are built in the form of trigonometric polynomials, Fourier coefficients of which are calculated by weighted averaging of PCRP realization. The pr
45#
發(fā)表于 2025-3-29 08:27:02 | 只看該作者
46#
發(fā)表于 2025-3-29 13:43:43 | 只看該作者
47#
發(fā)表于 2025-3-29 15:55:24 | 只看該作者
48#
發(fā)表于 2025-3-29 22:14:32 | 只看該作者
https://doi.org/10.1007/978-3-531-90776-50 and can be considered as a continuous extension of the autoregressive model of order one, AR(1). Furthermore, the OU process in finance it is known as the Vasicek model and is mainly used in interest rate modelling. Furthermore, it is deeply studied and its main properties are well known. However,
49#
發(fā)表于 2025-3-30 03:17:30 | 只看該作者
https://doi.org/10.1007/978-3-531-90776-5. In recent years many methods based on statistical properties of the signal have arisen. From the mathematical perspective the problem reduces to segmentation of the raw signal into parts with different features. Having the knowledge of the particular P-wave onset moment (for couple differently loc
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