TY - JOUR
T1 - A multi-factor analysis of forecasting methods
T2 - A study on the M4 competition
AU - Agathangelou, Pantelis
AU - Trihinas, Demetris
AU - Katakis, Ioannis
PY - 2020/4
Y1 - 2020/4
N2 - As forecasting becomes more and more appreciated in situations and activities of everyday life that involve prediction and risk assessment, more methods and solutions make their appearance in this exciting arena of uncertainty. However, less is known about what makes a promising or a poor forecast. In this article, we provide a multi-factor analysis on the forecasting methods that participated and stood out in the M4 competition, by focusing on Error (predictive performance), Correlation (among different methods), and Complexity (computational performance). The main goal of this study is to recognize the key elements of the contemporary forecasting methods, reveal what made them excel in the M4 competition, and eventually provide insights towards better understanding the forecasting task.
AB - As forecasting becomes more and more appreciated in situations and activities of everyday life that involve prediction and risk assessment, more methods and solutions make their appearance in this exciting arena of uncertainty. However, less is known about what makes a promising or a poor forecast. In this article, we provide a multi-factor analysis on the forecasting methods that participated and stood out in the M4 competition, by focusing on Error (predictive performance), Correlation (among different methods), and Complexity (computational performance). The main goal of this study is to recognize the key elements of the contemporary forecasting methods, reveal what made them excel in the M4 competition, and eventually provide insights towards better understanding the forecasting task.
KW - Forecasting
KW - Machine learning
KW - Predictive analytics
KW - Statistics
UR - http://www.scopus.com/inward/record.url?scp=85083844748&partnerID=8YFLogxK
U2 - 10.3390/data5020041
DO - 10.3390/data5020041
M3 - Article
AN - SCOPUS:85083844748
SN - 2306-5729
VL - 5
JO - Data
JF - Data
IS - 2
M1 - 41
ER -