Results 241 to 250 of about 421,961 (294)

Penalised Spline Estimation of Covariate-Specific Time-Dependent ROC Curves. [PDF]

Stat Med
Rodríguez-Álvarez MX, Inácio V.
europepmc   +1 more source

Shifting Cancer Landscapes in Korea: Divergent Incidence Trajectories, Sex-Specific Burdens, and Projected Case Counts for 24 Major Cancer Types from 1999 to 2023, with Forecasts to 2030. [PDF]

Curr Oncol
Jung H, Jung M.
europepmc   +1 more source

Improvement for exponential smoothing

, 2009
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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

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Exponential smoothing — I

Operations Research Letters, 1984
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Robert M Oliver
exaly   +2 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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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
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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
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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.
openaire   +1 more source