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Surrogate space based dimension reduction for nonignorable nonresponse 期刊论文
COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2022, 卷号: 168, 页码: 18
作者:  Deng, Jianqiu;  Yang, Xiaojie;  Wang, Qihua
收藏  |  浏览/下载：171/0  |  提交时间：2022/04/02
Sufficient dimension reduction  Nonignorable nonresponse  Cumulative mean estimation  Exponential tilting model  Regression calibration  Surrogate subspace  
A beyond multiple robust approach for missing response problem 期刊论文
COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2021, 卷号: 155, 页码: 13
作者:  Wang, Qihua;  Su, Miaomiao;  Wang, Ruoyu
收藏  |  浏览/下载：159/0  |  提交时间：2021/04/26
Model misspecification  Curse of dimension  Inverse probability weight  Imputation  
A rank-based approach to estimating monotone individualized two treatment regimes 期刊论文
COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2020, 卷号: 151, 页码: 12
作者:  Zhang, Haixiang;  Huang, Jian;  Sun, Liuquan
收藏  |  浏览/下载：180/0  |  提交时间：2020/09/23
Generalized regression  Individualized treatment rule  Outlier  Personalized medicine  Rank correlation  
Quantile regression in big data: A divide and conquer based strategy 期刊论文
COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2020, 卷号: 144, 页码: 17
作者:  Chen, Lanjue;  Zhou, Yong
收藏  |  浏览/下载：176/0  |  提交时间：2020/05/24
Data stream  Divide and conquer  Estimating equation  Massive data sets  Quantile regression  
Function-on-function quadratic regression models 期刊论文
COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2020, 卷号: 142, 页码: 14
作者:  Sun, Yifan;  Wang, Qihua
收藏  |  浏览/下载：184/0  |  提交时间：2020/05/24
Functional data analysis  Quadratic regression  Functional principal component analysis  Test of significance  Asymptotics  
Generalized endpoint-inflated binomial model 期刊论文
COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2015, 卷号: 89, 页码: 97-114
作者:  Tian, Guo-Liang;  Ma, Huijuan;  Zhou, Yong;  Deng, Dianliang
收藏  |  浏览/下载：135/0  |  提交时间：2018/07/30
Endpoint-inflated binomial distribution  Expectation-maximization algorithm  Multinomial logistic regression model  Stochastic representation  Zero-inflated binomial distribution