StandardStandard

Forecasting with a hybrid method utilizing data smoothing, a variation of the Theta method and shrinkage of seasonal factors. / Spiliotis, Evangelos; Assimakopoulos, Vassilios; Nikolopoulos, Konstantinos.

Yn: International Journal of Production Economics, Cyfrol 209, 03.2019.

Allbwn ymchwil: Cyfraniad at gyfnodolynErthygl

HarvardHarvard

APA

CBE

MLA

VancouverVancouver

Author

Spiliotis, Evangelos ; Assimakopoulos, Vassilios ; Nikolopoulos, Konstantinos. / Forecasting with a hybrid method utilizing data smoothing, a variation of the Theta method and shrinkage of seasonal factors. Yn: International Journal of Production Economics. 2019 ; Cyfrol 209.

RIS

TY - JOUR

T1 - Forecasting with a hybrid method utilizing data smoothing, a variation of the Theta method and shrinkage of seasonal factors

AU - Spiliotis, Evangelos

AU - Assimakopoulos, Vassilios

AU - Nikolopoulos, Konstantinos

PY - 2019/3

Y1 - 2019/3

N2 - In this paper, we discuss how extrapolation can be advanced by using some of the most successful elements and paradigms from the forecasting literature. We propose a new hybrid method that utilises: a) the decomposition approach of the Theta method, but instead of considering a linear trend we allow for nonlinear trends, b) rather than employing the extrapolation method on the raw data, we first apply smoothing to the data, and c) when seasonality is present, we employ the shrinkage approach to the derived indices instead of simply applying classical seasonal decomposition. We empirically evaluate the new proposition in the M3-Competition data with very promising results in terms of forecast accuracy.

AB - In this paper, we discuss how extrapolation can be advanced by using some of the most successful elements and paradigms from the forecasting literature. We propose a new hybrid method that utilises: a) the decomposition approach of the Theta method, but instead of considering a linear trend we allow for nonlinear trends, b) rather than employing the extrapolation method on the raw data, we first apply smoothing to the data, and c) when seasonality is present, we employ the shrinkage approach to the derived indices instead of simply applying classical seasonal decomposition. We empirically evaluate the new proposition in the M3-Competition data with very promising results in terms of forecast accuracy.

KW - Extrapolation

KW - Theta model

KW - Smoothing

KW - Shrinkage

KW - M3-competition

U2 - 10.1016/j.ijpe.2018.01.020

DO - 10.1016/j.ijpe.2018.01.020

M3 - Article

VL - 209

JO - International Journal of Production Economics

JF - International Journal of Production Economics

SN - 0925-5273

ER -