A proposed novel adaptive DC technique for non-stationary data removal.

Autor:	Musbah H; Department of Electrical and Computer Engineering, Dalhousie University, Halifax, Canada., Aly HH; Department of Electrical and Computer Engineering, Dalhousie University, Halifax, Canada., Little TA; Department of Electrical and Computer Engineering, Dalhousie University, Halifax, Canada.
Jazyk:	angličtina
Zdroj:	Heliyon [Heliyon] 2023 Feb 21; Vol. 9 (3), pp. e13903. Date of Electronic Publication: 2023 Feb 21 (Print Publication: 2023).
DOI:	10.1016/j.heliyon.2023.e13903
Abstrakt:	The stationarity of a time series is an important assumption in the Box-Jenkins methodology. Removing the non-stationary feature from the time series can be done using a differencing technique or a logarithmic transformation approach, but it is not guaranteed from the first step. This paper proposes a new adaptive DC technique, a novel technique for removing a non-stationary time series from the first step. The technique involves transferring non-stationary data into another domain that deals with it as a stationary time series, as it is much easier to be forecasted in that domain. The adaptive DC technique has been applied to different time series, including gasoline and diesel fuel prices, temperature, demand side, inflation rate and number of internet users time series. The performance of the proposed technique is evaluated using different statistical tests, including Augmented Dickey-Fuller (ADF), Kwiatkowski-Phillips-Schmidt-Shin (KPSS), and Phillips Perron (PP). Additionally, the technique is validated by comparing it with a differencing technique, and the results show that the proposed technique slightly outperforms the differencing method. The importance of the proposed technique is its capability to get the stationarity data from the first step, whereas the differencing technique sometimes needs more than one step. Competing Interests: The authors declare no conflict of interest. (© 2023 The Authors. Published by Elsevier Ltd.)
Databáze:	MEDLINE
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