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This tutorial explains the basics of linear regression models. especially low-order polynomials. and the corresponding statistical designs. namely, designs of resolution III, IV, V, and Central Composite Designs (CCDs).This tutorial assumes 'white noise', which means that the residuals of the...
Persistent link: https://www.econbiz.de/10011091274
Abstract: Prediction under model uncertainty is an important and difficult issue. Traditional prediction methods (such … as pretesting) are based on model selection followed by prediction in the selected model, but the reported prediction and … the reported prediction variance ignore the uncertainty from the selection procedure. This paper proposes a weighted …
Persistent link: https://www.econbiz.de/10011091622
This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable...
Persistent link: https://www.econbiz.de/10011092158