Model selection for the localized mixture of experts models |
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Authors: | Yunlu Jiang Yu Conglian Ji Qinghua |
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Affiliation: | 1. Department of Statistics, College of Economics, Jinan University, Guangzhou, People's Republic of China;2. School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, People's Republic of China |
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Abstract: | In this paper, we propose a penalized likelihood method to simultaneous select covariate, and mixing component and obtain parameter estimation in the localized mixture of experts models. We develop an expectation maximization algorithm to solve the proposed penalized likelihood procedure, and introduce a data-driven procedure to select the tuning parameters. Extensive numerical studies are carried out to compare the finite sample performances of our proposed method and other existing methods. Finally, we apply the proposed methodology to analyze the Boston housing price data set and the baseball salaries data set. |
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Keywords: | Localized mixture of experts models EM algorithm SCAD penalty function |
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