Prediction Intervals for ARIMA Models
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Other versions of this item:
- Snyder, R.D. & Ord, J.K. & Koehler, A.B., 1997. "Prediction Intervals for Arima Models," Monash Econometrics and Business Statistics Working Papers 8/97, Monash University, Department of Econometrics and Business Statistics.
References listed on IDEAS
- Moffitt, Robert, 1992. "Incentive Effects of the U.S. Welfare System: A Review," Journal of Economic Literature, American Economic Association, vol. 30(1), pages 1-61, March.
- Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Theory," Econometrica, Econometric Society, vol. 52(3), pages 681-700, May.
- Keane, Michael & Moffitt, Robert, 1998.
"A Structural Model of Multiple Welfare Program Participation and Labor Supply,"
International Economic Review,
Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(3), pages 553-589, August.
- M. Keane & R. Moffitt, "undated". "A structural model of multiple welfare program participation and labor supply," Institute for Research on Poverty Discussion Papers 1080-96, University of Wisconsin Institute for Research on Poverty.
- M. Keane & R. Mofitt, 1995. "A Structural Model of Multiple Welfare Program Participation and Labor Supply," Working Papers 95-4, Brown University, Department of Economics.
- Michael P. Keane & Robert A. Moffitt, 1995. "A structural model of multiple welfare program participation and labor supply," Working Papers 557, Federal Reserve Bank of Minneapolis.
- Hausman, J. A. & Abrevaya, Jason & Scott-Morton, F. M., 1998. "Misclassification of the dependent variable in a discrete-response setting," Journal of Econometrics, Elsevier, vol. 87(2), pages 239-269, September.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Koehler, Anne B. & Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "A study of outliers in the exponential smoothing approach to forecasting," International Journal of Forecasting, Elsevier, vol. 28(2), pages 477-484.
- Rob Hyndman & Muhammad Akram & Blyth Archibald, 2008. "The admissible parameter space for exponential smoothing models," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 60(2), pages 407-426, June.
- Luis Uzeda, 2016. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," ANU Working Papers in Economics and Econometrics 2016-632, Australian National University, College of Business and Economics, School of Economics.
- J Keith Ord & Ralph D Snyder & Anne B Koehler & Rob J Hyndman & Mark Leeds, 2005. "Time Series Forecasting: The Case for the Single Source of Error State Space," Monash Econometrics and Business Statistics Working Papers 7/05, Monash University, Department of Econometrics and Business Statistics.
- Forbes, C.S. & Snyder, R.D. & Shami, R.S., 2000. "Bayesian Exponential Smoothing," Monash Econometrics and Business Statistics Working Papers 7/00, Monash University, Department of Econometrics and Business Statistics.
- Ralph D. Snyder, 2004. "Exponential Smoothing: A Prediction Error Decomposition Principle," Monash Econometrics and Business Statistics Working Papers 15/04, Monash University, Department of Econometrics and Business Statistics.
- Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
More about this item
- C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
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