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- W2899472681 abstract "Abstract Considering model averaging estimation under multinomial and ordered logit models, we propose a weight choice method by minimizing an M -fold cross-validation criterion. Unlike Jackknife model averaging in Hansen and Racine (2012), our method deletes one group observations instead of deleting only one observation. Therefore, under the maximum likelihood estimation framework, the computational cost of our method is greatly reduced. We prove the asymptotic optimality of the proposed model averaging estimator under certain assumptions. The simulation results show that our proposed method produces more accurate forecasts than other model selection and averaging methods." @default.
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- W2899472681 date "2019-01-01" @default.
- W2899472681 modified "2023-10-18" @default.
- W2899472681 title "Averaging estimators for discrete choice by <mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML display=inline overflow=scroll id=d1e600 altimg=si2.gif><mml:mi>M</mml:mi></mml:math>-fold cross-validation" @default.
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- W2899472681 doi "https://doi.org/10.1016/j.econlet.2018.10.014" @default.
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