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Variable Selection for Varying Coefficient Models Via Kernel Based Regularized Rank Regression 被引量:1
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作者 kang-ning wang Lu LIN 《Acta Mathematicae Applicatae Sinica》 SCIE CSCD 2020年第2期458-470,共13页
A robust and efficient shrinkage-type variable selection procedure for varying coefficient models is proposed,selection consistency and oracle properties are established.Furthermore,a BIC-type criterion is suggested f... A robust and efficient shrinkage-type variable selection procedure for varying coefficient models is proposed,selection consistency and oracle properties are established.Furthermore,a BIC-type criterion is suggested for shrinkage parameter selection and theoretical property is discussed.Numerical studies and real data analysis also are included to illustrate the finite sample performance of our method. 展开更多
关键词 RANK regression oracle property variable selection ASYMPTOTIC RELATIVE efficiency BIC-type CRITERION
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