SCAD

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  • 期刊=Acta Mathematicae Applicatae Sinicax
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Partial Penalized Empirical Likelihood Ratio Test Under Sparse Case
《Acta Mathematicae Applicatae Sinica》2017年第2期327-344,共18页Shan-shan WANG Heng-jian CUI 
supported in part by the National Natural Science Foundation of China(Grant Nos.11471223,11231010,11028103,11071022,11501586,71420107025);Key project of Beijing Municipal Education Commission(Grant No.KZ201410028030);the Foundation of Beijing Center for Mathematics and Information Interdisciplinary Sciences
A consistent test via the partial penalized empirical likelihood approach for the parametric hy- pothesis testing under the sparse case, called the partial penalized empirical likelihood ratio （PPELR） test, is propo...
关键词：Chi-squared distribution empirical likelihood partial penalized empirical likelihood SCAD SPARSE 
Variable Selection in the Partially Linear Errors-in-Variables Models for Longitudinal Data
《Acta Mathematicae Applicatae Sinica》2012年第4期769-780,共12页Yi-ping YANG Liu-gen XUE Wei-hu CHENG 
Supported by the National Natural Science Foundation of China (Nos.11126332 and 11101452);the National Social Science Foundation of China (No.11CTJ004);the Natural Science Foundation Project of CQ CSTC(No.cstc2011jjA00014);the Research Foundation of Chongqing Municipal Education Commission (No.KJ110720)
This paper proposes a new approach for variable selection in partially linear errors-in-variables （EV） models for longitudinal data by penalizing appropriate estimating functions. We apply the SCAD penalty to simult...
关键词：ERRORS-IN-VARIABLES variable selection estimating function ORACLE SCAD 
Variable Selection for Generalized Varying Coefficient Partially Linear Models with Diverging Number of Parameters被引量：1
《Acta Mathematicae Applicatae Sinica》2012年第2期237-246,共10页Zheng-yan Lin Yu-ze Yuan 
Supported by the National Natural Science Foundation of China (No. 10871177);Specialized Research Fund for the Doctoral Program of Higher Education (No. 20090101110020)
Semiparametric models with diverging number of predictors arise in many contemporary scientific areas. Variable selection for these models consists of two components： model selection for non-parametric components and...
关键词：generalized linear model varying coefficient high dimensionality SCAD basis function. 
Local Linear Regression for Data with AR Errors
《Acta Mathematicae Applicatae Sinica》2009年第3期427-444,共18页Runze Li Yan Li 
supported by National Institute on Drug Abuse grant R21 DA024260;Yan Li issupported by National Science Foundation grant DMS 0348869 as a graduate research assistant
In many statistical applications, data are collected over time, and they are likely correlated. In this paper, we investigate how to incorporate the correlation information into the local linear regression. Under the ...
关键词：Auto-regressive error local linear regression partially linear model profile least squares SCAD 
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