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ORCIDKeming Yu
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2020 – today
- 2025
[j22]Ling-Nan Tai, Li Tao, Jianxin Pan, Man-Lai Tang, Keming Yu, Wolfgang Karl Härdle, Maozai Tian:
Fully nonparametric inverse probability weighting estimation with nonignorable missing data and its extension to missing quantile regression. Comput. Stat. Data Anal. 206: 108127 (2025)- 2024
- [j21]Yuanqi Chu
, Keming Yu:
Bayesian log-linear beta-negative binomial integer-valued Garch model. Comput. Stat. 39(3): 1183-1202 (2024) - 2023
- [j20]Yuanqi Chu, Zhouping Yin, Keming Yu:
Bayesian scale mixtures of normals linear regression and Bayesian quantile regression with big data and variable selection. J. Comput. Appl. Math. 428: 115192 (2023) - 2022
- [j19]Xueping Hu, Jingya Wang, Liuliu Wang, Keming Yu:
K-Nearest Neighbor Estimation of Functional Nonparametric Regression Model under NA Samples. Axioms 11(3): 102 (2022) - [j18]Rong Jiang, Keming Yu:
Renewable quantile regression for streaming data sets. Neurocomputing 508: 208-224 (2022) - 2021
- [j17]Rong Jiang, Keming Yu:
Smoothing quantile regression for a distributed system. Neurocomputing 466: 311-326 (2021) - [j16]Shiwang Hou, Keming Yu:
A non-parametric CUSUM control chart for process distribution change detection and change type diagnosis. Int. J. Prod. Res. 59(4): 1166-1186 (2021) - 2020
- [j15]Zhouping Yin, Keming Yu, Yuanzhi Wang:
Robust control algorithm and simulation of networked control systems. Comput. Commun. 157: 394-401 (2020) - [j14]Rong Jiang, Keming Yu:
Single-index composite quantile regression for massive data. J. Multivar. Anal. 180: 104669 (2020)
2010 – 2019
- 2019
- [j13]Mengmeng Sun, Tao Ding, Xu-Qing Tang, Keming Yu:
An Efficient Mixed-Model for Screening Differentially Expressed Genes of Breast Cancer Based on LR-RF. IEEE ACM Trans. Comput. Biol. Bioinform. 16(1): 124-130 (2019) - [c2]Sian Liu, Jingzhi Yu, Jing Zhuang, Keming Yu:
A Method to Determine Angle Kappa via Automated Shape Recognition from Surgical Images. ICHI 2019: 1-3 - 2018
- [j12]Hadeel S. Klakattawi, Veronica Vinciotti, Keming Yu:
A Simple and Adaptive Dispersion Regression Model for Count Data. Entropy 20(2): 142 (2018) - 2016
- [j11]Hussein Hashem, Veronica Vinciotti, Rahim Alhamzawi, Keming Yu:
Quantile regression with group lasso for classification. Adv. Data Anal. Classif. 10(3): 375-390 (2016) - [j10]Qifa Xu, Xi Liu, Cuixia Jiang, Keming Yu:
Quantile autoregression neural network model with applications to evaluating value at risk. Appl. Soft Comput. 49: 1-12 (2016) - 2015
- [j9]Wei Dang, Keming Yu:
Density Regression Based on Proportional Hazards Family. Entropy 17(6): 3679-3691 (2015) - [j8]Rima Sheikh Rajab, Milan Drazic, Nenad Mladenovic, Pavle Mladenovic, Keming Yu:
Fitting censored quantile regression by variable neighborhood search. J. Glob. Optim. 63(3): 481-500 (2015) - 2014
- [j7]Bing Xing Wang, Keming Yu, Zhuo Sheng:
New Inference for Constant-Stress Accelerated Life Tests With Weibull Distribution and Progressively Type-II Censoring. IEEE Trans. Reliab. 63(3): 807-815 (2014) - 2013
- [j6]Rahim Alhamzawi, Keming Yu:
Conjugate priors and variable selection for Bayesian quantile regression. Comput. Stat. Data Anal. 64: 209-219 (2013) - [j5]Jie Jiang, Xinsheng Liu, Keming Yu:
Maximum likelihood estimation of multinomial probit factor analysis models for multivariate t-distribution. Comput. Stat. 28(4): 1485-1500 (2013) - [j4]Dries F. Benoit, Rahim Alhamzawi, Keming Yu:
Bayesian lasso binary quantile regression. Comput. Stat. 28(6): 2861-2873 (2013) - 2010
- [j3]Tracy Zhou Wu, Keming Yu, Yan Yu:
Single-index quantile regression. J. Multivar. Anal. 101(7): 1607-1621 (2010) - [j2]Bing Xing Wang, Keming Yu, M. C. Jones:
Inference Under Progressively Type II Right-Censored Sampling for Certain Lifetime Distributions. Technometrics 52(4): 453-460 (2010)
2000 – 2009
- 2009
- [j1]Colin Chen, Keming Yu:
Automatic Bayesian quantile regression curve fitting. Stat. Comput. 19(3): 271-281 (2009)
1990 – 1999
- 1997
- [c1]David J. Hand, Keming Yu, Niall M. Adams:
Asessing and Improving Classification Rules. AISTATS 1997: 243-254
Coauthor Index
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