| A unified variable selection approach for varying coefficient models Y Tang, HJ Wang, Z Zhu, X Song Statistica Sinica, 601-628, 2012 | 71 | 2012 |
| Variable selection in quantile varying coefficient models with longitudinal data Y Tang, HJ Wang, Z Zhu Computational Statistics & Data Analysis 57 (1), 435-449, 2013 | 70 | 2013 |
| Pacific North American circulation pattern links external forcing and North American hydroclimatic change over the past millennium Z Liu, Y Tang, Z Jian, CJ Poulsen, JM Welker, GJ Bowen Proceedings of the National Academy of Sciences 114 (13), 3340-3345, 2017 | 44 | 2017 |
| Risk factor selection in rate making: EM adaptive LASSO for zero‐inflated Poisson regression models Y Tang, L Xiang, Z Zhu Risk Analysis 34 (6), 1112-1127, 2014 | 43 | 2014 |
| Variable selection in high-dimensional quantile varying coefficient models ZZ Y Tang, X Song, HJ Wang Journal of Multivariate Analysis 122, 115-132, 2013 | 35 | 2013 |
| Understanding key factors affecting power systems resilience L Shen, Y Tang, LC Tang Reliability Engineering & System Safety 212, 107621, 2021 | 34 | 2021 |
| An informative subset-based estimator for censored quantile regression Y Tang, HJ Wang, X He, Z Zhu Test 21, 635-655, 2012 | 30 | 2012 |
| Sequential Change Point Detection in Linear Quantile Regression Models YT Mi Zhou, Huixia Judy Wang Statistics & Probability Letters 100, 98-103, 2015 | 23 | 2015 |
| Improve estimation efficiency in quantile regression with longitudinal data JLWQ Yanlin Tang, Yinfeng Wang Journal of Statistical Planning and Inference 165, 38-55, 2015 | 18 | 2015 |
| Robust quantile analysis for accelerated life test data N Chen, Y Tang, ZS Ye IEEE Transactions on Reliability 65 (2), 901-913, 2015 | 17 | 2015 |
| Bayesian quantile nonhomogeneous hidden Markov models H Liu, X Song, Y Tang, B Zhang Statistical Methods in Medical Research 30 (1), 112-128, 2021 | 12 | 2021 |
| Composite Estimation for Single‐Index Models with Responses Subject to Detection Limits Y Tang, HJ Wang, H Liang Scandinavian Journal of Statistics 45 (3), 444-464, 2018 | 12 | 2018 |
| Conditional marginal test for high dimensional quantile regression Y Tang, Y Wang, HJ Wang, Q Pan Statistica Sinica 32 (2), 869-892, 2022 | 11 | 2022 |
| Copula-based semiparametric models for spatiotemporal data Y Tang, HJ Wang, Y Sun, AS Hering Biometrics 75 (4), 1156-1167, 2019 | 11 | 2019 |
| Variable Selection via Composite Quantile Regression with Dependent Errors ZZ Yanlin Tang, Xinyuan Song Statistica Neerlandica 69, 1-20, 2015 | 11 | 2015 |
| Paired or partially paired two-sample tests with unordered samples Y Wang, Y Tang, ZS Ye Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2022 | 9 | 2022 |
| Copula‐based semiparametric analysis for time series data with detection limits F Li, Y Tang, HJ Wang Canadian Journal of Statistics 47 (3), 438-454, 2019 | 9 | 2019 |
| Testing for the presence of significant covariates through conditional marginal regression Y Tang, HJ Wang, E Barut Biometrika 105 (1), 57-71, 2018 | 8 | 2018 |
| Penalized Regression Across Multiple Quantiles Under Random Censoring YTHJ Wang Journal of Multivariate Analysis 141, 132-146, 2015 | 8 | 2015 |
| Weighted quantile regression in varying-coefficient model with longitudinal data F Lin, Y Tang, Z Zhu Computational Statistics & Data Analysis 145, 106915, 2020 | 6 | 2020 |
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