دورية أكاديمية

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

التفاصيل البيبلوغرافية
العنوان: A proposed novel adaptive DC technique for non-stationary data removal
المؤلفون: Hmeda Musbah, Hamed H. Aly, Timothy A. Little
المصدر: Heliyon, Vol 9, Iss 3, Pp e13903- (2023)
بيانات النشر: Elsevier, 2023.
سنة النشر: 2023
المجموعة: LCC:Science (General)
LCC:Social sciences (General)
مصطلحات موضوعية: Science (General), Q1-390, Social sciences (General), H1-99
الوصف: 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.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2405-8440
Relation: http://www.sciencedirect.com/science/article/pii/S2405844023011106; https://doaj.org/toc/2405-8440
DOI: 10.1016/j.heliyon.2023.e13903
URL الوصول: https://doaj.org/article/871935f5ba5e4f1a847fb2326e33ff00
رقم الأكسشن: edsdoj.871935f5ba5e4f1a847fb2326e33ff00
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:24058440
DOI:10.1016/j.heliyon.2023.e13903