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A pedants approach to exponential smoothing [PDF]
, 2005 An approach to exponential smoothing that relies on a linear single source of error state space model is outlined. A maximum likelihood method for the estimation of associated smoothing parameters is developed. Commonly used restrictions on the smoothing parameters are rationalised.
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The Optimality of General-Order Exponential Smoothing
Operations Research, 1974This paper derives the class of nonstationary time-series representations for which exponential smoothing of arbitrary order minimizes mean-square forecast error. It points out that these representations are included in the class of integrated moving averages developed by Box and Jenkins, permitting various procedures to be applied to estimating the ...
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Exponential smoothing with regressors: Estimation and initialization
Model Assisted Statistics and Applications, 2015The main objective of this paper is to outline the estimation and initialization procedures for the exponential smoothing with regressors forecasting approach which was recently introduced. The paper also discusses what restrictions need to be imposed during the estimation process so that the algorithm satisfies the forecastability conditions.
Ahmad Farid Osman, Maxwell L. King
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Proceedings of the workshop on Virtual environments 2003, 2003
We present novel algorithms for predictive tracking of user position and orientation based on double exponential smoothing. These algorithms, when compared against Kalman and extended Kalman filter-based predictors with derivative free measurement models, run approximately 135 times faster with equivalent prediction performance and simpler ...
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We present novel algorithms for predictive tracking of user position and orientation based on double exponential smoothing. These algorithms, when compared against Kalman and extended Kalman filter-based predictors with derivative free measurement models, run approximately 135 times faster with equivalent prediction performance and simpler ...
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2008
In earlier chapters we have considered only univariate models; we now proceed to examine multi-series extensions and to compare the multi-series innovations models with other multi-series schemes. We shall refer to our approach as the vector exponential smoothing (VES) framework. The innovations framework is similar to the structural time series models
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In earlier chapters we have considered only univariate models; we now proceed to examine multi-series extensions and to compare the multi-series innovations models with other multi-series schemes. We shall refer to our approach as the vector exponential smoothing (VES) framework. The innovations framework is similar to the structural time series models
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Robust methods in exponential smoothing
Kybernetika, 1996The paper investigates the robust modification of exponential smoothing with additive outliers. Motivated by the recursive methods described by \textit{T. Cipra} [``Robust exponential smoothing'', J. Forecasting 11, 57-69 (1992)], the author applies the \(M\)-estimates approach to perform the robust modification. Simple and double exponential smoothing
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Exponential smoothing models for energy forecasting
2013In this paper we address the issue of modelling and forecasting spot electricity* prices and energy l,oad demand. In particular, we model hourly time series for the Italian 'GM3, (G.rtore Mercato Elettrico) and Nordic Nord Pool markets. Exponential smoothing Holt-Winters methods are appropriate in this context because they are highly adaptable and ...
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Adaptive Exponential Smoothing
1977Abstract : The adaptive exponential smoothing technique, and its utility for international affairs analysis, is discussed. Both monitoring and forecasting aspects of the technique are described. Calculation procedures are illustrated and worked through in an example using international event/interaction data.
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