Work

Theory and Application of James-Stein Seasonal Forecasting Model for Short Time Series

Year: 2014

Type: conference-paper

Abstract: Accurate seasonal forecasting plays an important role in product demand forecast.This paper gives an insight into the theory of a James-Stein seasonal forecasting model.The conditions in which the method outperforms the classical decomposition method are then presented.The conditions show that James-Stein model has more accurate prediction results when dealing with large noise data.The conclusion is then examined through a set of real data from M-competition.The experimental results confirm the practical value of the theory.

Source: Advances in intelligent systems research/Advances in Intelligent Systems Research

DOI: 10.2991/lemcs-14.2014.220

Authors: Hui Mao, Kui Zhang

Institution: Wuhan Polytechnic University

Language: English

Topic: Forecasting Techniques and Applications

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: hybrid

OpenAlex ID: W2086917210

FWCI:

Cites: 15

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Related to: 10