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.

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Year of publication:	2000-08
Authors:	Forbes, C.S. ; Snyder, R.D. ; Shami, R.S.
Institutions:	Department of Econometrics and Business Statistics, Monash Business School
Subject:	Time series analysis \| forecasting \| structural model \| local level model \| prediction interval

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Extent:	application/pdf
Series:	Monash Econometrics and Business Statistics Working Papers.
Type of publication:	Book / Working Paper
Language:	English
Notes:	Number 7/00 21 pages
Classification:	C11 - Bayesian Analysis ; C22 - Time-Series Models ; C51 - Model Construction and Estimation
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005125279