Weiping Zhang--Research

国家自然科学基金项目"混合多响应纵向数据的均值相关结构同时统计推断方法研究",2017.1- 2020.12
国家自然科学基金项目"纵向数据分析中的有效统计推断方法及其应用",2013.1- 2016.12
国家青年科学基金项目"高通量基因数据分析中的 Bayes 统计方法"2009.1-2011.12
中国科学技术大学青年基金项目"统计推断中的Bayes分析及其应用",2006.1-2008.12

STATISTICS PUBLICATIONS

Hu W. and Zhang W. (2024) Flexible Bayesian Quantile Regression based on the Generalized Asymmetric Huberised-type Distribution, Statistics and Computing, 34(5), 144.

Shao L., Wu J., Zhang W. and Chen Y. (2024) Integrated Subgroup Identification from Multi-source Data, Computational Statistics and Data Analysis, 193, 107918.

Gong T., Zhang W., Chen Y. (2023) Uncovering block structures in large rectangular matrices, Journal of Multivariate Analysis. 198, 105211

Zhang W, Li Y, Chen Y, Tang C Y. (2023) Parsimonious Gaussian copula modelling through constrained Cholesky decomposition for data with temporal dependence (in Chinese). Sci Sin Math, 2023, 53(5): 777–790.

Shu L., Chen Y., Zhang W. and Wang X. (2022) Spatial rank-based high-dimensional change point detection via random integration. Journal of Multivariate Analysis 189, 104942

Zhang W., Zhao D., Chen Y} (2022) Regression Estimation for longitudinal Data with Nonignorable Intermittent Nonresponse and Dropout. Communications in Mathematics and Statistics.10, 383–411.

Chen Y., Wang J., Zhang W. (2022) Tail distortion risk measure for portfolio with multivariate regularly variation. Communications in Mathematics and Statistics,10, 263–285

Zhang, W. Jin B., Bai Z. (2021) Learning Block Structure in U-statistic Based Large Correlation Matrices. Biometrika, 108(4):933-946.

Qian F, Zhang, W. Chen Y. (2021) Adaptive Banding Covariance Estimation for High-dimensional Multivariate Longitudinal Data. The Canadian Journal of Statistics, 49(3):906-938

Hu J., Chen Y., Zhang, W. Guo X. (2021) Penalized high-dimensional M-quantile regression: From L1 to Lp optimization. The Canadian Journal of Statistics, 49(3):875-905

Chen Y., Hu J. and Zhang, W. * (2020) Too Connected to Fail? Evidence from a Chinese Financial Risk Spillover Network , China \& World Economy, 28(6):78-100.

Zhang, W. *, Xie, F. and Tan J. (2020) A Robust Joint Modeling Approach for Longitudinal Data with Informative Dropouts, Computational Statistics, 35(4), 1759-1783

Zhao W., Zhang W. \& Lian H. (2020) Marginal quantile regression for varying coefficient models with longitudinal data, Ann Inst Stat Math. 72:213–234

Zhang, F., Zhang, W. , Li, R., Lian, H. (2020) Faster convergence rate for functional linear regression in reproducing kernel Hilbert spaces, Statistics, 54:167-181.

Zhang W. , Wang J., Qian F., Chen Y.* (2020) A joint mean-correlation modeling approach for longitudinal zero-inflated count data, Brazilian Journal of Probability and Statistics, 34(1):35–50.

Qian F., Chen Y., Zhang, W. (2020) Regularized Estimation of Precision Matrix for High-dimensional Multivariate Longitudinal Data. Journal of Multivariate Analysis, 176:104580.

Zhang, W. , Zhang M. and Chen Y*. (2020) A copula-based GLMM model for multivariate longitudinal data with mixed-types of responses, Sankhya B, Volume 82-B, Part 2, pp. 353-379

Cui Di, Zhang Weiping. Bayesian variable selection for proportional hazards model with current status data[J]. Journal of University of Science and Technology of China, 2020, 50(10): 1303-1314.

LI Yezhen, ZHANG Weiping. A Cholesky factor model in correlation modeling for discrete longitudinal data[J]. Journal of University of Science and Technology of China, 2020, 50(9): 1266-1276.

Tan Jiaxin, Zhang Weiping. A robust joint modeling approach for longitudinal data.Journal of University of Science and Technology of China,2020,50(03):317-327+348.

Tang, C. Y., Zhang, W. and Leng, C. (2019) Discrete longitudinal data modeling with a mean-correlation regression approach. Statistica Sinica, 29:853-876.

Lin H., Jiang X., Lian H., Zhang, W. (2019) Reduced rank modeling for functional regression with functional responses. Journal of Multivariate Analysis, Vol. 169(01)205-217.

Chen, Y., Gao, Y., Gao, W. Zhang, W. (2018) Second-Order Asymptotics of the Risk Concentration of a Portfolio with Deflated Risks, Mathematical Problems in Engineering, 1-12.

Zhang, W., Leng, C., and Tang, C. Y. (2015). A joint modeling approach for longitudinal studies. Journal of the Royal Statistical Society Series B, 77(1):219–238.

Zhang, W.,Liu, Y. and Li， R. (2015). Joint Modeling of Mean-Covariance Structures Based on Partial Autocorrelation for Longitudinal Data. Journal of Applied Probability and Statistics,31(6): 582-595..

Liu M. and Zhang, W. .Bayesian Joint Semiparametric Mean-Covariance Modeling for Longitudinal Data.

Leng, C. and Zhang, W. (2014). Smoothing combined estimating equations in quantile regression for longitudinal data. Statistics and Computing, 24(1):123-136.

Xing, X., Liu, M. and Zhang, W. (2013). Joint Semiparametric Mean-Covariance modeling by Moving Average Cholesky Decomposition for Longitudinal Data, Journal of University of Science and Technology of China, 43(8):607-621.

Liu, X. and Zhang, W. (2013). A moving average Cholesky factor model in joint mean-covariance modeling for longitudinal data, Science in China A, Vol56(11): 2367-2379.

Weiping Zhang, Chenlei Leng (2012) A Moving Average Cholesky Factor Model in Covariance Modeling for Longitudinal Data, Biometrika, 99:141-150.

Weiping Zhang, Laisheng Wei, Yu Chen (2012), The Superiorities of Bayes Linear Unbiased Estimator in Multivariate Linear Models, Acta Mathematica Applicatae Sinica, 28(2), 383:394.

Weiping Zhang, Laisheng Wei, Yu Chen (2011), The Superiorities of Bayes Linear Unbiased Estimation in Partitioned Linear model, Jrl Syst Sci & Complexity, 24: 945–954

Chenlei Leng,Weiping Zhang, Jianxin Pan (2010), Semiparametric Mean-Covariance Regression Analysis for Longitudinal Data, Journal of the American Statistical Association, Vol.105, No. 489: 181-193.

Weiping Zhang, Yu Chen (2010) , Double Sampling Method for Genetic Association Analysis with Differential Genotyping Errors, Biostatistics, Bioinformatics and Biomathematics, Vol1,43-54.

Chen, Yu; Zhang, Weiping; and Liu, Jie (2010) Asymptotic Tail Probability of Randomly Weighted Sum of Dependent Heavy-Tailed Random Variables, Asia-Pacific Journal of Risk and Insurance: Vol.4 :Iss. 2.

Weiping Zhang, Nien-fan Zhang, Hung-kung Liu (2009), A generalized method for the multiple artifacts problem in interlaboratory comparisons with linear trends, Metrologia, 46:345-350.

Z. Q. J. Lu, N. D. Lowhorn, W. Wong-Ng, W. Zhang, et. al. (2009) Statistical Analysis of a Round-Robin Measurement Survey of Two Candidate Materials for a Seebeck Coefficient Standard Reference Material, J. Res. Natl. Inst. Stand. Technol. 114, 37-55.

Lowhorn, N.D.; Wong-Ng, W.; Zhang, W.; Lu, Z.Q.; Otani, M.; et al. (2009) Round-robin measurements of two candidate materials for a Seebeck coefficient Standard Reference Material, Applied Physics A: Materials Science & Processing,Vol94, No.2:231-234

Zhang Weiping, Wei Laisheng (2008), The superiority of empirical Bayes estimation of parameters in partitioned normal linear model, Acta. Math. Scientia, 28B(4):955-962.

霍涉云, 张伟平, 韦来生 (2007), 一类线性模型参数的Bayes估计及其优良性, 中国科技大学学报, 37(7): 773-776

张伟平, 韦来生 (2007), 错误先验假定下Bayes线性无偏估计的稳健性, 应用概率统计, 23(1): 59-67.

Laisheng Wei, Weiping Zhang (2007), The Superiorities of Bayes Linear Minimum Risk Estimation in Linear Model, Communication in statistics—theory and methods, 36(5): 917-926.

Yu Chen, Weiping Zhang (2007), Large deviations for random sums of negatively dependent random variables with consistently varying tails. Statist.Prob.Lett.77, 530-538.

张伟平, 韦来生 (2005), 单向分类随机效应模型中方差分量的渐近最优经验Bayes估计, 系统科学与数学, 25(1): 106-117.

Wei Laisheng, Zhang Weiping (2005), Empirical Bayes test problems of variance components in random effect model, Acta. Math. Scientia, 25B(2):274-282..

Zhang Weiping, Wei Laisheng, Yang Yaning (2005), The superiority of empirical Bayes estimator of parameters in linear model, Statist. Prob. Lett. 72:43-50.

Zhang Weiping, Wei Laisheng (2005), On Bayes linear unbiased estimation of estimable functions for the singular linear model, Sci. in China, A. 48(7): 898-903.