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Title: A novel ranking procedure for forecasting approaches using Data Envelopment Analysis
Authors: Emrouznejad, Ali
Rostami-Tabar, Bahman
Petridis, Konstantinos
Type: Article
Subjects: FRASCATI::Natural sciences::Mathematics::Applied Mathematics
FRASCATI::Natural sciences::Mathematics::Statistics and probability
Issue Date: 2016
Source: Technological Forecasting and Social Change
Volume: 111
First Page: 235
Last Page: 243
Abstract: To compare the accuracy of different forecasting approaches an error measure is required. Many error measures have been proposed in the literature, however in practice there are some situations where different measures yield different decisions on forecasting approach selection and there is no agreement on which approach should be used. Generally forecasting measures represent ratios or percentages providing an overall image of how well fitted the forecasting technique is to the observations. This paper proposes a multiplicative Data Envelopment Analysis (DEA) model in order to rank several forecasting techniques. We demonstrate the proposed model by applying it to the set of yearly time series of the M3 competition. The usefulness of the proposed approach has been tested using the M3-competition where five error measures have been applied in and aggregated to a single DEA score.
ISSN: 00401625
Other Identifiers: 10.1016/j.techfore.2016.07.004
Appears in Collections:Department of Applied Informatics

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