EconPapers    
Economics at your fingertips  
 

Prediction intervals for exponential smoothing using two new classes of state space models

Anne B. Koehler, Rob Hyndman (), Ralph Snyder () and Keith Ord ()
Additional contact information
Anne B. Koehler: Miami University, USA, Postal: Miami University, USA

Journal of Forecasting, 2005, vol. 24, issue 1, 17-37

Abstract: Three general classes of state space models are presented, using the single source of error formulation. The first class is the standard linear model with homoscedastic errors, the second retains the linear structure but incorporates a dynamic form of heteroscedasticity, and the third allows for non-linear structure in the observation equation as well as heteroscedasticity. These three classes provide stochastic models for a wide variety of exponential smoothing methods. We use these classes to provide exact analytic (matrix) expressions for forecast error variances that can be used to construct prediction intervals one or multiple steps ahead. These formulas are reduced to non-matrix expressions for 15 state space models that underlie the most common exponential smoothing methods. We discuss relationships between our expressions and previous suggestions for finding forecast error variances and prediction intervals for exponential smoothing methods. Simpler approximations are developed for the more complex schemes and their validity examined. The paper concludes with a numerical example using a non-linear model. Copyright © 2005 John Wiley & Sons, Ltd.

Date: 2005
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (26) Track citations by RSS feed

Downloads: (external link)
http://hdl.handle.net/10.1002/for.938 Link to full text; subscription required (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:jof:jforec:v:24:y:2005:i:1:p:17-37

Access Statistics for this article

Journal of Forecasting is currently edited by Derek W. Bunn

More articles in Journal of Forecasting from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing ().

 
Page updated 2019-10-16
Handle: RePEc:jof:jforec:v:24:y:2005:i:1:p:17-37