Applied integration of time series and multi-variable regression algorithms
İstatistikçiler Dergisi:İstatistik ve Aktüerya, cilt.14, sa.1, ss.13-25, 2021 (TRDizin)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 14 Sayı: 1
- Basım Tarihi: 2021
- Dergi Adı: İstatistikçiler Dergisi:İstatistik ve Aktüerya
- Derginin Tarandığı İndeksler: TR DİZİN (ULAKBİM)
- Sayfa Sayıları: ss.13-25
- Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
- Ankara Yıldırım Beyazıt Üniversitesi Adresli: Evet
Özet
Time Series (TS) based prediction models generate prediction based data that is supposed to be similar to the future data at a certain level. In this study, we designed new modeling that increases the prediction performance of the TS algorithm. The main purpose of the new modeling is to integrate the Multivariate-Adaptive-Regression-Splines (MARSplines) algorithm into the TS algorithm. Five-year Tokyo Stock Exchange data is analyzed as a case study to apply the relevant models. The results show that the new regression-based approach significantly improves the prediction performance of the time series algorithm.