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作 者:Xian-hui LIU Zhan-feng WANG Yao-hua WU
机构地区:[1]Department of Statistics and Finance,University of Science and Technology of China [2]School of Statistics and Research Center of Applied Statistics,Jiangxi University of Finance and Economics
出 处:《Acta Mathematicae Applicatae Sinica》2019年第2期421-434,共14页应用数学学报(英文版)
基 金:partially supported by National Natural Science Foundation of China(Grant No.11101396);Anhui Provincial Natural Science Foundation(Grant No.1908085MA06)
摘 要:Censored regression("Tobit") model is a special case of limited dependent variable regression model, and plays an important role in econometrics. Based on this model, all kinds of methods for variable or group variable selection have been developed and the corresponding shrinkage parameter estimates are widely studied. However, asymptotic distributions of the shrinkage estimates involve unknown nuisance parameters,such as density function of error term. To avoid estimating nuisance parameters, this paper presents a randomly weighting method to approximate to the asymptotic distribution of the shrinkage estimate. A computation procedure of random approximation is provided and asymptotic properties of the randomly weighting estimates are also obtained. The proposed methods are evaluated with extensively numerical studies and a women labor supply example.Censored regression("Tobit") model is a special case of limited dependent variable regression model, and plays an important role in econometrics. Based on this model, all kinds of methods for variable or group variable selection have been developed and the corresponding shrinkage parameter estimates are widely studied. However, asymptotic distributions of the shrinkage estimates involve unknown nuisance parameters,such as density function of error term. To avoid estimating nuisance parameters, this paper presents a randomly weighting method to approximate to the asymptotic distribution of the shrinkage estimate. A computation procedure of random approximation is provided and asymptotic properties of the randomly weighting estimates are also obtained. The proposed methods are evaluated with extensively numerical studies and a women labor supply example.
关 键 词:Censored regression model VARIABLE SELECTION ASYMPTOTIC properties randomly weighting
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