Cited by 5,757Forecasting Techniques and ApplicationsTime Series Analysis and ForecastingStatistical and numerical algorithms

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Another look at measures of forecast accuracy

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Hyndman, Rob J., Koehler, Anne B.·2006·International Journal of Forecasting

DOI 10.1016/j.ijforecast.2006.03.001

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Forecasting methods and applications
(1993) · Computers & Operations Research · doi:10.1016/0305-0548(93)90040-p · Cited by 2,393
Analysis of Financial Time Series
(2006) · Technometrics · doi:10.1198/tech.2006.s405 · Cited by 2,382
Principles of Forecasting
Armstrong, J. S. (2001) · International series in management science/operations research/International series in operations research & management science · doi:10.1007/978-0-306-47630-3 · Cited by 1,962
The M3-Competition: results, conclusions and implications
Makridakis, S., & Hibon, M. (2000) · International Journal of Forecasting · doi:10.1016/s0169-2070(00)00057-1 · Cited by 1,701
The accuracy of extrapolation (time series) methods: Results of a forecasting competition
Makridakis, S., Andersen, A. P., Carbone, R., Fildes, R. A., Hibon, M., Lewandowski, R., Newton, J., Parzen, E., & Winkler, R. L. (1982) · Journal of Forecasting · doi:10.1002/for.3980010202 · Cited by 1,465
Error measures for generalizing about forecasting methods: Empirical comparisons
Armstrong, J. S., & Collopy, F. (1992) · International Journal of Forecasting · doi:10.1016/0169-2070(92)90008-w · Cited by 1,415
Applied Economic Forecasting
Ruist, E., & Theil, H. (1967) · Ekonomisk Tidskrift · doi:10.2307/3439127 · Cited by 1,224
A state space framework for automatic forecasting using exponential smoothing methods
Hyndman, R. J., Koehler, A. B., Snyder, R. D., & Grose, S. D. (2002) · International Journal of Forecasting · doi:10.1016/s0169-2070(01)00110-8 · Cited by 1,076
Self-citation
Analysis of Financial Time Series
Tsay, R. S. (2002) · Wiley series in probability and statistics · doi:10.1002/0471264105 · Cited by 903
Accuracy measures: theoretical and practical concerns
Makridakis, S. (1993) · International Journal of Forecasting · doi:10.1016/0169-2070(93)90079-3 · Cited by 883

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Armstrong, 2001, Evaluating forecasting methods, Chapter 14

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Authors: Hyndman, R. J., & Koehler, A. B.
Affiliations: Monash University (AU)
Miami University (US)
Corresponding author: Hyndman, Rob J.
ORCID: Hyndman, Rob J.
Venue: International Journal of Forecasting
Publisher: Elsevier BV
Published: 2006-10
Volume: 22
Issue: 4
Pages: 679-688
ISSN: 0169-2070 (ISSN-L)
DOI: 10.1016/j.ijforecast.2006.03.001
OpenAlex: W2016210396
Cited by: 5,757
References: 34
Citations by year: 2026: 870 · 2025: 557 · 2024: 451 · 2023: 430 · 2022: 477 · 2021: 612 · 2020: 439 · 2019: 358 · 2018: 325 · 2017: 263 · 2016: 245 · 2015: 185 · 2014: 169 · 2013: 125 · 2012: 80
FWCI: 28.03
Type: journal article
Language: en
Open access: green
figshare.com
Licence: cc-by
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: International Journal of Forecasting (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
Figshare (submittedVersion, cc-by)
Monash University
Topics: Social Sciences › Decision Sciences › Management Science and Operations Research › Forecasting Techniques and Applications
Physical Sciences › Computer Science › Signal Processing › Time Series Analysis and Forecasting
Physical Sciences › Mathematics › Applied Mathematics › Statistical and numerical algorithms
Keywords: forecast accuracy measures, univariate time series forecasting, M3 competition

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