Automatic ARIMA modeling including interventions, using time series expert software
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Makridakis, Spyros & Hibon, Michele & Lusk, Ed & Belhadjali, Moncef, 1987. "Confidence intervals: An empirical investigation of the series in the M-competition," International Journal of Forecasting, Elsevier, vol. 3(3-4), pages 489-508.
- Rossana, Robert J & Seater, John J, 1995.
"Temporal Aggregation and Economic Time Series,"
Journal of Business & Economic Statistics, American Statistical Association, vol. 13(4), pages 441-451, October.
- John J. Seater & Robert J. Rossana, "undated". "Temporal Aggregation and Economic Time Series," Working Paper Series 19, North Carolina State University, Department of Economics.
- Tashman, Leonard J., 2000. "Out-of-sample tests of forecasting accuracy: an analysis and review," International Journal of Forecasting, Elsevier, vol. 16(4), pages 437-450.
- Chatfield, Chris, 1993. "Calculating Interval Forecasts: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 143-144, April.
- Chatfield, Chris, 1993. "Calculating Interval Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(2), pages 121-135, April.
- Tashman, Leonard J. & Leach, Michael L., 1991. "Automatic forecasting software: A survey and evaluation," International Journal of Forecasting, Elsevier, vol. 7(2), pages 209-230, August.
- Laurence Broze & Guy Melard, 1990. "Exponential smoothing: estimation by maximum likelihood," ULB Institutional Repository 2013/13716, ULB -- Universite Libre de Bruxelles.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Melard, G. & Pasteels, J. -M., 2000. "Automatic ARIMA modeling including interventions, using time series expert software," International Journal of Forecasting, Elsevier, vol. 16(4), pages 497-508.
- Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
- De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
- Jan G. De Gooijer & Rob J. Hyndman, 2005.
"25 Years of IIF Time Series Forecasting: A Selective Review,"
Monash Econometrics and Business Statistics Working Papers
12/05, Monash University, Department of Econometrics and Business Statistics.
- Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
- Saoud, Patrick & Kourentzes, Nikolaos & Boylan, John E., 2022. "Approximations for the Lead Time Variance: a Forecasting and Inventory Evaluation," Omega, Elsevier, vol. 110(C).
- Tashman, Leonard J., 2000. "Out-of-sample tests of forecasting accuracy: an analysis and review," International Journal of Forecasting, Elsevier, vol. 16(4), pages 437-450.
- Berrin Aytac & S. Wu, 2013. "Characterization of demand for short life-cycle technology products," Annals of Operations Research, Springer, vol. 203(1), pages 255-277, March.
- Lee, Yun Shin & Scholtes, Stefan, 2014. "Empirical prediction intervals revisited," International Journal of Forecasting, Elsevier, vol. 30(2), pages 217-234.
- repec:lan:wpaper:470 is not listed on IDEAS
- Charles, Amelie & Darne, Olivier & Kim, Jae, 2016.
"Stock Return Predictability: Evaluation based on Prediction Intervals,"
MPRA Paper
70143, University Library of Munich, Germany.
- Amélie Charles & Olivier Darné & Jae H. Kim, 2016. "Stock Return Predictability: Evaluation based on prediction intervals," Working Papers hal-01295037, HAL.
- Dhaoui, Iyad, 2015. "Climat des Affaires et Compétitivité de l’Entreprise Tunisienne Après la Révolution : Analyses et Perspectives [Business Climate and Competitiveness of the Tunisian Enterprise After the Revolution:," MPRA Paper 87331, University Library of Munich, Germany.
- Pascual, Lorenzo & Romo, Juan & Ruiz, Esther, 2005.
"Bootstrap prediction intervals for power-transformed time series,"
International Journal of Forecasting, Elsevier, vol. 21(2), pages 219-235.
- Pascual, Lorenzo & Romo, Juan & Ruiz Ortega, Esther, 2001. "Bootstrap prediction intervals for power-transformed time series," DES - Working Papers. Statistics and Econometrics. WS ws010503, Universidad Carlos III de Madrid. Departamento de EstadÃstica.
- Li, Yushu & Andersson, Jonas, 2014. "A Likelihood Ratio and Markov Chain Based Method to Evaluate Density Forecasting," Discussion Papers 2014/12, Norwegian School of Economics, Department of Business and Management Science.
- Klaus Abberger, 2006.
"Kernel smoothed prediction intervals for ARMA models,"
Statistical Papers, Springer, vol. 47(1), pages 1-15, January.
- Abberger, Klaus, 2002. "Kernel smoothed prediction intervals for ARMA models," CoFE Discussion Papers 02/02, University of Konstanz, Center of Finance and Econometrics (CoFE).
- Roberto Buizza & James W. Taylor, 2004. "A comparison of temperature density forecasts from GARCH and atmospheric models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(5), pages 337-355.
- Yushu Li & Jonas Andersson, 2020. "A likelihood ratio and Markov chain‐based method to evaluate density forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 47-55, January.
- James W. Taylor & Derek W. Bunn, 1999. "A Quantile Regression Approach to Generating Prediction Intervals," Management Science, INFORMS, vol. 45(2), pages 225-237, February.
- Wolfgang Nierhaus, 2019. "Business Cycle 2018: Forecast and Reality," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 72(03), pages 22-29, February.
- Harvey, David I. & Newbold, Paul, 2003. "The non-normality of some macroeconomic forecast errors," International Journal of Forecasting, Elsevier, vol. 19(4), pages 635-653.
- Mirakyan, Atom & Meyer-Renschhausen, Martin & Koch, Andreas, 2017. "Composite forecasting approach, application for next-day electricity price forecasting," Energy Economics, Elsevier, vol. 66(C), pages 228-237.
- Makridakis, Spyros & Spiliotis, Evangelos & Assimakopoulos, Vassilios & Chen, Zhi & Gaba, Anil & Tsetlin, Ilia & Winkler, Robert L., 2022. "The M5 uncertainty competition: Results, findings and conclusions," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1365-1385.
More about this item
Keywords
ARIMA models; Expert system; Intervention analysis; M3-competition; Outliers;All these keywords.
JEL classification:
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ulb:ulbeco:2013/13744. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Benoit Pauwels (email available below). General contact details of provider: https://edirc.repec.org/data/ecsulbe.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.