工程数学学报
工程數學學報
공정수학학보
CHINESE JOURNAL OF ENGINEERING MATHEMATICS
2014年
1期
139-151
,共13页
变量选择%最小二乘%缺失数据%Oracle性质%SCAD
變量選擇%最小二乘%缺失數據%Oracle性質%SCAD
변량선택%최소이승%결실수거%Oracle성질%SCAD
variable selection%least squares%missing data%Oracle property%SCAD
考虑协变量随机缺失下部分线性模型，采用惩罚加权最小二乘提出了一种变量选择方法，研究了所提出方法的有限样本性质，证明了非零系数的估计具有Oracle性质。进一步，基于局部线性逼近方法给出了一步稀疏估计。通过模拟研究了所提出方法的有限样本性质。
攷慮協變量隨機缺失下部分線性模型，採用懲罰加權最小二乘提齣瞭一種變量選擇方法，研究瞭所提齣方法的有限樣本性質，證明瞭非零繫數的估計具有Oracle性質。進一步，基于跼部線性逼近方法給齣瞭一步稀疏估計。通過模擬研究瞭所提齣方法的有限樣本性質。
고필협변량수궤결실하부분선성모형，채용징벌가권최소이승제출료일충변량선택방법，연구료소제출방법적유한양본성질，증명료비령계수적고계구유Oracle성질。진일보，기우국부선성핍근방법급출료일보희소고계。통과모의연구료소제출방법적유한양본성질。
A partial linear model with covariate data missing at random is considered. A strategy for variable selection is proposed by penalizing the weighted least squares. The sampling properties for the proposed procedure are investigated. Furthermore, the proposed estimators of the nonzero coefficients are shown to have the asymptotic oracle property. In addition, a one-step sparse estimator is considered by the local linear approximation for the penalty function. The finite sample behavior of the proposed method is evaluated with a simulation study.
