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We provide a new approach to automatic forecasting based on an extended range of exponential smoothing methods. Each method in our taxonomy of exponential smoothing methods provides forecasts that are equivalent to forecasts from a state space model. This equivalence allows: (1) easy calculation of the likelihood, the AIC and other model selection criteria;(More)
We discuss and compare measures of accuracy of univariate time series forecasts. The methods used in the M-competition and the M3-competition, and many of the measures recommended by previous authors on this topic, are found to be inadequate, and many of them are degenerate in commonly occurring situations. Instead, we propose that the mean absolute scaled(More)
Nuclear pore complexes (NPCs) are anchoring sites of intranuclear filaments of 3-6 nm diameter that are coaxially arranged on the perimeter of a cylinder and project into the nuclear interior for lengths varying in different kinds of cells. Using a specific monoclonal antibody we have found that a polypeptide of approximately 190 kD on SDS-PAGE, which(More)
A new approach is proposed for forecasting a time series with multiple seasonal patterns. A state space model is developed for the series using the single source of error approach which enables us to develop explicit models for both additive and multiplicative seasonality. Parameter estimates may be obtained using methods adapted from general exponential(More)
Three general classes of state space models are presented, based upon the single source of error formulation. The first class is the standard linear state space model with homoscedastic errors, the second retains the linear structure but incorporates a dynamic form of heteroscedasticity, and the third allows for non-linear structure in the observation(More)
Integrin-mediated force application induces a conformational change in latent TGF-β1 that leads to the release of the active form of the growth factor from the extracellular matrix (ECM). Mechanical activation of TGF-β1 is currently understood as an acute process that depends on the contractile force of cells. However, we show that ECM remodeling, preceding(More)
Applications of exponential smoothing to forecasting time series usually rely on three basic methods: simple exponential smoothing, trend corrected exponential smoothing and a seasonal variation thereof. A common approach to selecting the method appropriate to a particular time series is based on prediction validation on a withheld part of the sample using(More)