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math.ST2018
High Dimensional Robust Inference for Cox Regression Models
Shengchun Kong, Zhuqing Yu, Xianyang Zhang +1
We consider high-dimensional inference for potentially misspecified Cox proportional hazard models based on low dimensional results by Lin and Wei [1989]. A de-sparsified Lasso est…
math.ST2017
High Dimensional Inference in Partially Linear Models
Ying Zhu, Zhuqing Yu, Guang Cheng
We propose two semiparametric versions of the debiased Lasso procedure for the model , where is high dimensional but sparse (exactly or approxi…
math.ST2016
Minimax Optimal Estimation in Partially Linear Additive Models under High Dimension
Zhuqing Yu, Michael Levine, Guang Cheng
In this paper, we derive minimax rates for estimating both parametric and nonparametric components in partially linear additive models with high dimensional sparse vectors and smoo…