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Arief Gusnanto
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Mathematics

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MODEL AVERAGING, AN ALTERNATIVE APPROACH TO MODEL SELECTION IN HIGH DIMENSIONAL DATA ESTIMATION Deiby T. Salaki; Anang Kurnia; Arief Gusnanto; I Wayan Mangku; Bagus Sartono
FORUM STATISTIKA DAN KOMPUTASI Vol. 20 No. 2 (2015)
Publisher : FORUM STATISTIKA DAN KOMPUTASI

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Abstract

Model averaging is an alternative approach to classical model selection in model estimation. The model selection such as forward or stepwise regression, use certain criteria in choosing one best model fitted the data such as AIC and BIC. On the other hand, model averaging estimates one model whose parameters determined by weighted averaging the parameter of each approximation models. Instead of conducting inference and prediction only based one best chosen model, model averaging covering model uncertainty problem by including all possible model in determining prediction model. Some of its developments and applications also challenges will be described in this paper. Frequentist model averaging will be preferential described.Keywords : model selection, frequentist model averaging, high dimensional data
Co-Authors Anang Kurnia Bagus Sartono Deiby T Salaki I Wayan Mangku