The DOI matches its Crossref record; 33 of the 34 references it cites were found in a registry or an index.
Another look at measures of forecast accuracy
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In the citing paper
“MAE and MAPE are commonly used measures in ML [9] and provide a more natural and intuitive measure of model performance [12,13].”
From Turnaround time prediction for clinical chemistry samples using machine learning (2022) · cites this paper as [12]
Citations
Cites
Forecasting methods and applications
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Analysis of Financial Time Series
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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
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-citationAnalysis 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
Forecasting: Methods and Applications
Briggs, W. M., Makridakis, S., Wheelwright, S. C., Hyndman, R. J., & Diebold, F. X. (1999) · Journal of the American Statistical Association · doi:10.2307/2669717 · Cited by 626
Self-citationPrinciples of Forecasting. A Handbook for Researchers and Practitioners
Devezas, T. (2002) · Technological Forecasting and Social Change · doi:10.1016/s0040-1625(02)00180-4 · Cited by 523
The theta model: a decomposition approach to forecasting
Assimakopoulos, V., & Nikolopoulos, K. I. (2000) · International Journal of Forecasting · doi:10.1016/s0169-2070(00)00066-2 · Cited by 507
Economic and Statistical Measures of Forecast Accuracy
Granger, C. W. J., & Pesaran, M. (1999) · Journal of Forecasting · doi:10.1002/1099-131x(200012)19:7 · Cited by 436
Diebold, F. X. (1997) · UCLA Biblioteca de Ingenieria Civil · Cited by 416
On the limitations of comparing mean square forecast errors
Clements, M. P., & Hendry, D. F. (1993) · Journal of Forecasting · doi:10.1002/for.3980120802 · Cited by 397
On the asymmetry of the symmetric MAPE
Goodwin, P., & Lawton, R. (1999) · International Journal of Forecasting · doi:10.1016/s0169-2070(99)00007-2 · Cited by 329
Exponential smoothing model selection for forecasting
Billah, B., King, M. L., Snyder, R. D., & Koehler, A. B. (2005) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2005.08.002 · Cited by 282
Self-citationThe evaluation of extrapolative forecasting methods
Fildes, R. A. (1992) · International Journal of Forecasting · doi:10.1016/0169-2070(92)90009-x · Cited by 268
Forecasting, time series, and regression : an applied approach
Bowerman, B. L., O'Connell, R. T., & Koehler, A. B. (2005) · Cited by 261
Self-citationForecasting: Methods and Applications, 3rd Ed
Makridakis, S., Wheelwright, S. C., & Hyndman, R. J. (1997) · Cited by 245
Self-citationRudd, R. W., & Theil, H. (1967) · Journal of Farm Economics · doi:10.2307/1237096 · Cited by 195
The M3 competition: Statistical tests of the results
Koning, A., Franses, P. H., Hibon, M., & Stekler, H. O. (2004) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2004.10.003 · Cited by 180
Hyndman, R. J., & Billah, B. (2002) · International Journal of Forecasting · doi:10.1016/s0169-2070(01)00143-1 · Cited by 157
Self-citationEvaluating Forecast Performance in an Inventory Control System
Gardner, E. S. (1990) · Management Science · doi:10.1287/mnsc.36.4.490 · Cited by 127
Apples, oranges and mean square error
Chatfield, C. (1988) · International Journal of Forecasting · doi:10.1016/0169-2070(88)90127-6 · Cited by 84
Error measures and the choice of a forecast method
Ahlburg, D. A. (1992) · International Journal of Forecasting · doi:10.1016/0169-2070(92)90010-7 · Cited by 65
A note on the measurement of accuracy for subnational demographic estimates
Swanson, D. A., Tayman, J., & Barr, C. F. (2000) · Demography · doi:10.2307/2648121 · Cited by 47
An MSE statistic for comparing forecast accuracy across series
Thompson, P. A. (1990) · International Journal of Forecasting · doi:10.1016/0169-2070(90)90007-x · Cited by 46
A model selection strategy for time series with increasing seasonal variation
Franses, P. H., & Koehler, A. B. (1998) · International Journal of Forecasting · doi:10.1016/s0169-2070(98)00041-7 · Cited by 43
Self-citationA commentary on error measures
Chatfield, C. (1992) · International Journal of Forecasting · doi:10.1016/0169-2070(92)90011-w · Cited by 40
Judgmental forecasting in the presence of loss functions
Lawrence, M. J., & O’Connor, M. J. (2004) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2004.02.003 · Cited by 33
Commentaries on the M3-Competition
(2001) · International Journal of Forecasting · doi:10.1016/s0169-2070(01)00119-4 · Cited by 22
Flagged first, then by citations
1 of the 34 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- Armstrong, 2001, Evaluating forecasting methods, Chapter 14
Cited by
Sorted by citations
Chicco, D., Warrens, M. J., & Jurman, G. (2021) · PeerJ Computer Science · doi:10.7717/peerj-cs.623 · Cited by 5,380
Automatic Time Series Forecasting: The forecast Package for R
Hyndman, R. J., & Khandakar, Y. (2008) · Journal of Statistical Software · doi:10.18637/jss.v027.i03 · Cited by 3,548
Self-citationElectricity price forecasting: A review of the state-of-the-art with a look into the future
Weron, R. (2014) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2014.08.008 · Cited by 1,646
Statistical and machine learning forecasting methods: Concerns and ways forward
Makridakis, S., Spiliotis, E., & Assimakopoulos, V. (2018) · PLOS ONE · doi:10.1371/journal.pone.0194889 · Cited by 1,528
Probabilistic electric load forecasting: A tutorial review
Hong, T., & Shu, F. (2016) · International Journal of Forecasting · doi:10.1016/j.ijforecast.2015.11.011 · Cited by 1,460
Metadata
- 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)
- 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
- 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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