Bayesian Exponential Smoothing
In this paper, a Bayesian version of the exponential smoothing method of forecasting is proposed. The approach is based on a state space model containing only a single source of error for each time interval. This model allows us to improve current practices surrounding exponential smoothing by providing both point predictions and measures of the uncertainty surrounding them.
|Date of creation:||Aug 2000|
|Contact details of provider:|| Postal: PO Box 11E, Monash University, Victoria 3800, Australia|
Phone: +61 3 99052489
Fax: +61 3 99055474
Web page: http://business.monash.edu/econometrics-and-business-statistics
More information through EDIRC
|Order Information:|| Web: http://business.monash.edu/econometrics-and-business-statistics Email: |
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Snyder, Ralph D & Ord, J Keith & Koehler, Anne B, 2001.
"Prediction Intervals for ARIMA Models,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 19(2), pages 217-225, April.
- 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.
- Harvey, Andrew & Snyder, Ralph D., 1990. "Structural time series models in inventory control," International Journal of Forecasting, Elsevier, vol. 6(2), pages 187-198, July.
- Ray, W. D., 1989. "Rates of convergence to steady state for the linear growth version of a dynamic linear model (DLM)," International Journal of Forecasting, Elsevier, vol. 5(4), pages 537-545.
- Makridakis, Spyros & Chatfield, Chris & Hibon, Michele & Lawrence, Michael & Mills, Terence & Ord, Keith & Simmons, LeRoy F., 1993. "The M2-competition: A real-time judgmentally based forecasting study," International Journal of Forecasting, Elsevier, vol. 9(1), pages 5-22, April.
- Snyder, R.D. & Koehler, A.B. & Ord, J.K., 1998. "Lead Time demand for Simple Exponential Smoothing," Monash Econometrics and Business Statistics Working Papers 13/98, Monash University, Department of Econometrics and Business Statistics.
- Ord, J.K. & Koehler, A. & Snyder, R.D., 1995. "Estimation and Prediction for a Class of Dynamic Nonlinear Statistical Models," Monash Econometrics and Business Statistics Working Papers 4/95, Monash University, Department of Econometrics and Business Statistics. Full references (including those not matched with items on IDEAS)
When requesting a correction, please mention this item's handle: RePEc:msh:ebswps:2000-7. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dr Xibin Zhang)
If references are entirely missing, you can add them using this form.