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Prediction Intervals for Exponential Smoothing State Space Models

Rob Hyndman (), A.B. Koehler, Keith Ord () and Ralph Snyder ()

No 11/01, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: The main objective of this paper is to provide analytical expression for forecast variances that can be used in prediction intervals for the exponential smoothing methods. These expressions are based on state space models with a single source of error that underlie the exponential smoothing methods. In cases where an ARIMA model also underlies an exponential smoothing method, there is an equivalent state space model with the same variance expression. We also discuss relationships between these new ideas and previous suggestions for finding forecast variances and prediction intervals for the exponential smoothing methods.

Keywords: Forecast distribution; Holt-Winters method; Structural models (search for similar items in EconPapers)
JEL-codes: C32 C53 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm and nep-ets
Date: 2001-12
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