EconPapers    
Economics at your fingertips  
 

Statistical Foundations of Exponential Smoothing

Ralph D. Snyder

No 266862, Department of Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: In this paper the exponential smoothing methods of forecasting are rationalized in terms of a statistical state space model with only one primary source of randomness. Their link, in general terms, with the ARMA class of models ( both stationary and nonstationary cases) is also explored.

Keywords: Research; Methods/Statistical; Methods (search for similar items in EconPapers)
Pages: 24
References: Add references at CitEc
Citations:

Downloads: (external link)
https://ageconsearch.umn.edu/record/266862/files/monash-069.pdf (application/pdf)
https://ageconsearch.umn.edu/record/266862/files/monash-069.pdf?subformat=pdfa (application/pdf)

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:ags:monebs:266862

DOI: 10.22004/ag.econ.266862

Access Statistics for this paper

More papers in Department of Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics Contact information at EDIRC.
Bibliographic data for series maintained by AgEcon Search ().

 
Page updated 2025-12-14
Handle: RePEc:ags:monebs:266862