Modified Holt's Linear Trend Method

YAPAR G., ÇAPAR S., TAYLAN SELAMLAR H., YAVUZ İ.

HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS, cilt.47, sa.5, ss.1394-1403, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 47 Sayı: 5
  • Basım Tarihi: 2018
  • Doi Numarası: 10.15672/hjms.2017.493
  • Dergi Adı: HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.1394-1403
  • Anahtar Kelimeler: Exponential smoothing, Forecasting, Initial value, M3-Competition, Smoothing parameter, TIME-SERIES, STATE, ACCURACY, ART
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Exponential smoothing models are simple, accurate and robust forecasting models and because of these they are widely applied in the literature. Holt's linear trend method is a valuable extension of exponential smoothing that helps deal with trending data. In this study we propose a modified version of Holt's linear trend method that eliminates the initialization issue faced when fitting the original model and simplifies the optimization process. The proposed method is compared empirically with the most popular forecasting algorithms based on exponential smoothing and Box-Jenkins ARIMA with respect to its predictive performance on the M3-Competition data set and is shown to outperform its competitors.