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Variable screening and model selection in censored quantile regression via sparse penalties and stepwise refinement

机译：通过稀疏惩罚和逐步细化在可审查分位数回归中进行变量筛选和模型选择

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作者
Gan, Lu;
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作者单位

University of Illinois at Urbana-Champaign;

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授予单位 University of Illinois at Urbana-Champaign;
学科
学位 Ph.D.
年度 2014
页码 90 p.
总页数 90
原文格式 PDF
正文语种 eng
中图分类
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2. Weighted composite quantile estimation and variable selection method for censored regression model [J] . Tang L., Zhou Z., Wu C. Statistics & Probability Letters . 2012,第3期

机译：删失回归模型的加权复合分位数估计与变量选择方法
3. VARIABLE SELECTION FOR SPARSE HIGH-DIMENSIONAL NONLINEAR REGRESSION MODELS BY COMBINING NONNEGATIVE GARROTE AND SURE INDEPENDENCE SCREENING [J] . Shuang Wu, Hongqi Xue, Yichao Wu, Statistica Sinica . 2014,第3期

机译：结合非线性负数和确定独立性筛选的稀疏高维非线性回归模型的变量选择
4. STEPWISE GROUP SPARSE REGRESSION (SGSR): GENE-SET-BASED PHARMACOGENOMIC PREDICTIVE MODELS WITH STEPWISE SELECTION OF FUNCTIONAL PRIORS1 [C] . IN SOCK JANG, RODRIGO DIENSTMANN, ADAM A.MARGOLIN, Pacific Symposium on Biocomputing . 2015

机译：逐步组稀疏回归（SGSR）：基于基于基于基于药物的药物替代方法预测模型，具有逐步选择功能性Priors1
5. REGRESSION ANALYSIS WITH SELECTION BIASED DEPENDENT VARIABLE (TRUNCATED DATA, STRATIFIED SAMPLES, CENSORED, KAPLAN-MEIR ESTIMATE, SEMI-PARAMETRIC MODEL) [D] . WANG, MEI-CHENG. 1985

机译：具有选择偏置相关变量的回归分析（截断的数据，分层的样本，经过检查的，Kaplan-Meier估计，半参数模型）
6. STEPWISE GROUP SPARSE REGRESSION (SGSR): GENE-SET-BASED PHARMACOGENOMIC PREDICTIVE MODELS WITH STEPWISE SELECTION OF FUNCTIONAL PRIORS [O] . IN SOCK JANG, RODRIGO DIENSTMANN, ADAM A. MARGOLIN, -1

机译：逐步组稀疏回归（SGSR）：基于基因组的药物遗传学预测模型具有功能优先级的逐步选择
7. An Additive Sparse Penalty for Variable Selection in High-Dimensional Linear Regression Model [O] . Sangin Lee 2015

机译：高维线性回归模型中可变选择的添加剂稀疏罚分

Variable screening and model selection in censored quantile regression via sparse penalties and stepwise refinement

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