Results 251 to 260 of about 27,723 (301)

Robust exponential smoothing [PDF]

Journal of Forecasting, 1992
AbstractThe paper is devoted to robust modifications of exponential smoothing for time series with outliers or long‐tailed distributions. Classical exponential smoothing applied to such time series is sensitive to the presence of outliers or long‐tailed distributions and may give inadequate smoothing and forecasting results.
Tomáš Cipra
exaly   +3 more sources

The Fundamental Theorem of Exponential Smoothing [PDF]

Operations Research, 1961
Exponential smoothing is a formalization of the familiar learning process, which is a practical basis for statistical forecasting. Higher orders of smoothing are defined by the operator Snt(x) = αSn−1t(x) + (1 − α) Snt−1(x), where S0t(x) = xt, 0 < α < 1.
Brown, Robert G., Meyer, Richard F.
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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.
Ralph D Snyder
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Bayesian Exponential Smoothing [PDF]

, 2000
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 an improvement to current practices in exponential smoothing by providing both point predictions and measures of the uncertainty
Forbes, C.S., Snyder, R.D., Shami, R.S.
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On the brown method of exponential smoothing

Operations Research Letters, 1982
In the literature the Brown Method is often recommended for forecasting with the smoothing constant @a = 0.1 or @a = 0.2. We describe an experiment for checking the recommendation, the results of which indicate that it has severe drawbacks. An alternative is suggested.
Y. V. Lirov, E. M. Levich
openaire   +2 more sources

IMAGE SMOOTHING WITH EXPONENTIAL FUNCTIONS

International Journal of Pattern Recognition and Artificial Intelligence, 2001
Noise reduction in images, also known as image smoothing, is an essential and first step before further processings of the image. The key to image smoothing is to preserve important features while removing noise from the image. Gaussian function is widely used in image smoothing.
Mitra Basu, Min Su
openaire   +1 more source

Exponential smoothing — I

Operations Research Letters, 1984
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An Analysis of General Exponential Smoothing

Operations Research, 1976
General exponential smoothing and adaptive smoothing are terms used to describe the application of discounted least squares to the fitting of certain mathematical functions to time series data. The technique yields forecasts satisfying simple recursive equations that generally contain fairly complex terms.
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The Optimality of General-Order Exponential Smoothing

Operations Research, 1974
This 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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Some comments on the initialization of exponential smoothing

Journal of Forecasting, 1984
AbstractIt is shown that the traditional choice for the initial smoothed statistics in general exponential smoothing leads to the same forecasts as the equivalent ARIMA model, provided that one uses zero starting values for the initial shocks. In addition, an initialization which uses ‘backforecasts’ as initial smoothed statistics is considered, and ...
Ledolter, Johannes, Abraham, B.
openaire   +2 more sources