Citations (25)
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Ye Tao & Juliang Yin. (2023) Maximum likelihood estimation for quantile autoregression models with Markovian switching. Communications in Statistics - Theory and Methods 52:22, pages 7915-7943.
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Rong Jiang, Shi Chen & Fu-Ya Wang. (2023) Quantile regression for massive data set. Communications in Statistics - Simulation and Computation 0:0, pages 1-9.
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Duo Zhang, Liucang Wu, Keying Ye & Min Wang. (2021) Bayesian quantile semiparametric mixed-effects double regression models. Statistical Theory and Related Fields 5:4, pages 303-315.
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Yanke Wu, Maozai Tian & Man-Lai Tang. (2020) General composite quantile regression: Theory and methods. Communications in Statistics - Theory and Methods 49:9, pages 2217-2236.
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Yuzhu Tian, Liyong Wang, Manlai Tang & Maozai Tian. (2020) Likelihood-based quantile mixed effects models for longitudinal data with multiple features via MCEM algorithm. Communications in Statistics - Simulation and Computation 49:2, pages 317-334.
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Yuzhu Tian, Liyong Wang, Manlai Tang, Yanchao Zang & Maozai Tian. (2020) Likelihood-based quantile autoregressive distributed lag models and its applications. Journal of Applied Statistics 47:1, pages 117-131.
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Yuzhu Tian, Manlai Tang, Liyong Wang & Maozai Tian. (2019) Bayesian bridge-randomized penalized quantile regression estimation for linear regression model with AP(q) perturbation. Journal of Statistical Computation and Simulation 89:15, pages 2951-2979.
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S. Ghasemzadeh, M. Ganjali & T. Baghfalaki. (2018) A Bayesian conditional model for bivariate mixed ordinal and skew continuous longitudinal responses using quantile regression. Journal of Applied Statistics 45:14, pages 2619-2642.
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Yuzhu Tian, Heng Lian & Maozai Tian. (2017) Bayesian composite quantile regression for linear mixed-effects models. Communications in Statistics - Theory and Methods 46:15, pages 7717-7731.
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Shen Zhang, Mai Dao, Keying Ye, Zifei Han & Min Wang. A novel Bayesian computational approach for bridge-randomized quantile regression in high dimensional models. Journal of Statistical Computation and Simulation 0:0, pages 1-20.
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Articles from other publishers (15)
Weidong Liu, Xiaojun Mao, Xiaofei Zhang & Xin Zhang. (2024) Efficient Sparse Least Absolute Deviation Regression With Differential Privacy. IEEE Transactions on Information Forensics and Security 19, pages 2328-2339.
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Fengkai Yang. (2023) Robust Procedure for Change-Point Estimation Using Quantile Regression Model with Asymmetric Laplace Distribution. Symmetry 15:2, pages 447.
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Luca Merlo, Antonello Maruotti & Lea Petrella. (2021) Two-part quantile regression models for semi-continuous longitudinal data: A finite mixture approach. Statistical Modelling 22:6, pages 485-508.
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Mai Dao, Min Wang & Souparno Ghosh. (2022) A novel Bayesian method for variable selection and estimation in binary quantile regression. Statistical Analysis and Data Mining: The ASA Data Science Journal 15:6, pages 766-780.
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Ye Tao & Juliang Yin. (2022) Markov switching quantile regression models with time-varying transition probabilities. Journal of the Korean Statistical Society 51:3, pages 803-830.
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Mai Dao, Min Wang, Souparno Ghosh & Keying Ye. (2022) Bayesian variable selection and estimation in quantile regression using a quantile-specific prior. Computational Statistics 37:3, pages 1339-1368.
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Christian E. Galarza, Panpan Zhang & Víctor H. Lachos. (2020) Logistic Quantile Regression for Bounded Outcomes Using a Family of Heavy-Tailed Distributions. Sankhya B 83:S2, pages 325-349.
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Yuzhu Tian & Xinyuan Song. (2020) Bayesian bridge-randomized penalized quantile regression. Computational Statistics & Data Analysis 144, pages 106876.
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Siamak Ghasemzadeh, Mojtaba Ganjali & Taban Baghfalaki. (2018) Bayesian quantile regression for analyzing ordinal longitudinal responses in the presence of non-ignorable missingness. METRON 76:3, pages 321-348.
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Yuzhu Tian, Manlai Tang, Yanchao Zang & Maozai Tian. (2018) Quantile regression for linear models with autoregressive errors using EM algorithm. Computational Statistics 33:4, pages 1605-1625.
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Fengkai Yang. (2017) A Stochastic EM Algorithm for Quantile and Censored Quantile Regression Models. Computational Economics 52:2, pages 555-582.
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Yanke Wu & Maozai Tian. (2017) An effective method to reduce the computational complexity of composite quantile regression. Computational Statistics 32:4, pages 1375-1393.
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Christian Galarza Morales, Victor Lachos Davila, Celso Barbosa Cabral & Luis Castro Cepero. (2017) Robust quantile regression using a generalized class of skewed distributions. Stat 6:1, pages 113-130.
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Yuzhu Tian, Qianqian Zhu & Maozai Tian. (2016) Estimation of linear composite quantile regression using EM algorithm. Statistics & Probability Letters 117, pages 183-191.
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Yuzhu Tian, Er’qian Li & Maozai Tian. (2016) Bayesian joint quantile regression for mixed effects models with censoring and errors in covariates. Computational Statistics 31:3, pages 1031-1057.
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