Evidence for the selection of forecasting methods

Nigel Meade

79 citations0/0 files storedJournal of Forecasting

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Forecasting Techniques and Applications Time Series Analysis and Forecasting Grey System Theory Applications

Abstract

Reid (1972) was among the first to argue that the relative accuracy of forecasting methods changes according to the properties of the time series. Comparative analyses of forecasting performance such as the M-Competition tend to support this argument. The issue addressed here is the usefulness of statistics summarizing the data available in a time series in predicting the relative accuracy of different forecasting methods. Nine forecasting methods are described and the literature suggesting summary statistics for choice of forecasting method is summarized. Based on this literature and further argument a set of these statistics is proposed for the analysis. These statistics are used as explanatory variables in predicting the relative performance of the nine methods using a set of simulated time series with known properties. These results are evaluated on observed data sets, the M-Competition data and Fildes Telecommunications data. The general conclusion is that the summary statistics can be used to select a good forecasting method (or set of methods) but not necessarily the best. Copyright © 2000 John Wiley & Sons, Ltd.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 79 citations exist upstream.

References

1977Time Series Analysis: Forecasting and Control 1983THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS 1982The accuracy of extrapolation (time series) methods: Results of a forecasting competition 1974Experience with Forecasting Univariate Time Series and the Combination of Forecasts 1979Accuracy of Forecasting: An Empirical Investigation 1985Forecasting Trends in Time Series 2007Rule-based Forecasting: Development and Validation of an Expert Systems Approach to Combining Time Series Extrapolations 1992The evaluation of extrapolative forecasting methods

Cited by

2002Modelling multinational telecommunications demand with limited data 2021FFORMPP: Feature-based forecast model performance prediction 2016Meta-learning with neural networks and landmarking for forecasting model selection an empirical evaluation of different feature sets applied to industry data 2014Aviation fuel demand development in China

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.