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  • 王占锋
  • 副教授
  • +86-551-63600560
  • zfw@ustc.edu.cn
  • 统计与金融系
  • 概率与统计
English
  • Incorporating graphical structure of predictors in sparse quantile regression , Journal of Business & Economic Statistics , 2021 , 39(3): 783-792
  • Sequential adaptive variables and subject selection for GEE methods , Biometrics , 2020 , 76(2): 496-507
  • Nonparametric random effects functional regression model using Gaussian process priors , Statistica Sinica , 2021 , 31(1): 53-78
  • A general robust t-process regression model , Computational Statistics and Data Analysis , 2021 , 154
  • Active learning in multiple-class classification problems via individualized binary models , Computational Statistics and Data Analysis , 2020 , 145
  • Tobit quantile regression of left-censored longitudinal data with informative observation times , Statistica Sinica , 2018 , 28: 527-548
  • Extended t-process regression models , Journal of Statistical Planning and Inference , 2017 , 189: 38-60
  • Group Variable Selection for Relative Error Regression , Journal of Statistical Planning and Inference , 2016 , 175: 40-50
  • Least product relative error estimation , Journal of Multivariate Analysis , 2016 , 144: 91-98
  • Random weighting approximation for Tobit regression models withlongitudinal data , Computational Statistics and Data Analysis , 2014 , 79: 235-247
  • Group variable selection and estimation in the tobit censored response model , Computational Statistics and Data Analysis , 2013 , 60: 80-89
  • Marker selection via maximizing the partial area under the ROC curve of linear risk scores , Biostatistics , 2011 , 12(2): 369-385
  • Minimum -divergence estimator and hierarchical testing in loglinear models under product-multinomial sampling , Journal of Statistical Planning and Inference , 2009 , 139: 3488-3500
  • A robust estimation for the extended t-process regression model , Statistics and Probability Letters , 2020 , 157
  • A relative error-based estimation with an increasing number of parameters , Communications in Statistics- Theory and Methods , 2018 , 47: 196-209
  • Tobit regression model with parameters of increasing dimensions , Statistics and Probability Letters , 2017 , 120: 1-7
  • Asymptotic properties of maximum likelihood estimator for two-step logit models , Statistics and Probability Letters , 2014 , 85: 135-143
  • A parsimonious threshold independent protein feature selection method through the area under receiver operating characteristic urve , Bioinformatics , 2007 , 23(20): 2788-2794
  • Bayesian Estimation for the Extended t -process Regression Models with Independent Errors , Communications in Mathematics and Statistics , 2021 , 9(3): 261-272
  • H-relative error estimation for multiplicative regression model with random effect , Computational Statistics , 2018 , 33: 623-638
  • Assessing the Diagnostic Power of Variables Measured with a Detection Limit , Computational Statistics , 2016 , 31: 1287-1303
  • A change-point problem in relative error-based regression , Test , 2015 , 24(5): 835-856
  • Assessing the predictive power of newly added biomarkers , Biometrical Journal , 2015 , 57(5): 797-807
  • A general AUC-type measure and biomarker selection , Statistics in Biopharmaceutical Research , 2014 , 6: 89-103
  • Sequential estimate for linear regression models with uncertain number of effective variables , Metrika , 2013 , 76(7): 949-978
  • Alignment of protein mass spectrometry data by integrated Markov chain shifting method , Statistics and Its Interface , 2009 , 2: 329-340
  • Distribution Approximation o f Shrinkage Estimate in Censored Regression Model via Randomly Weighting Method , Acta Mathematicae Applicatae Sinica , 2019 , 35(2): 421-434
  • A relative error estimation approach for multiplicative single index model , Journal of Systems Science and Complexity--English Series , 2017 , 30: 1160-1172
  • Sequential estimate for generalized linear regression models with uncertain number of effective variables , Journal of Systems Science and Complexity--English Series , 2015 , 28: 424-438
  • Identifying differential gene sets using the linear combination of genes with maximum AUC , Journal of Proteomics & Bioinformatics , 2012 , 5(3): 73-83
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