research interest

  • Mixture models
  • Longitudinal data analysis
  • Robust estimation
  • Variable selection
  • High dimensional modeling
  • Nonparametric and semiparametric modeling
  • Dimension reduction

    Weixin Yao, Ph.D. (CV)

    Associate Professor
    Department of Statistics
    1337 Olmsted Hall
    University of California, Riverside
    Riverside, CA 92521
    Phone: (951)827-6007

    I received my Ph.D. in 2007 from the Department of Statistics, The Pennsylvania State University, under the supervision of Dr. Bruce G. Lindsay and Dr. Runze Li.


    Research Interests

      Mixture models; Nonparametric and semiparametric modeling; Longitudinal data analysis; Robust estimation; High dimensional modeling; Variable selection; Dimension reduction.


    Editorial Services

    • Associate Editor, Biometrics (2018-present)
    • Associate Editor, Journal of Computational and Graphical Statistics (2018-present)
    • Associate Editor, Journal of Multivariate Analysis (2018-present)
    • Associate Editor, The American Statistician (2017-present)


    Selected Referred Publications(Full List)

    • Kurum, E., Li, R., Shiffman, S., and Yao, W. (2016). Time-Varying Coefficient Models for Joint Modeling Binary and Continuous Outcomes in Longitudinal Data. Statistica Sinica, 26, 979-1000. [pdf]
    • Yao, W. and Li, L. (2014). A New Regression Model: Modal Linear Regression. Scandinavian Journal of Statistics, 41, 656-671. [pdf]
    • Huang, M., Li, R., and Huang, H., and Yao, W. (2014). Estimating Mixture of Gaussian Processes by Kernel Smoothing. Journal of Business and Economics Statistics, 32, 259-270. [pdf]
    • Yao, W. and Li, R. (2013). New Local Estimation Procedure for Nonparametric Regression Function of Longitudinal Data. Journal of the Royal Statistical Society, Ser B., 75, 123-138. [pdf]
    • Huang, M. and Yao, W. (2012). Mixture of Regression Models with Varying Mixing Proportions: A Semiparametric Approach. Journal of American Statistical Association, 107, 711-724. [pdf]
    • Yao, W., Lindsay, B. G., and Li, R. (2012). Local modal regression. Journal of Nonparametric Statistics, 24, 647-663. The winner of The Journal of Nonparametric Statistics Best Paper Award in 2015. [pdf]
    • Yao, W. (2012). Model Based Labeling for Mixture Models. Statistics and Computing, 22, 337-347. [pdf]
    • Wang, Q. and Yao, W. (2012). An Adaptive Estimation of MAVE. Journal of Multivariate Data Analysis, 104, 88-100. [pdf]
    • Cao, J. and Yao, W. (2012). Semiparametric Mixture of Binomial Regression with a Degenerate Component. Statistica Sinica, 22, 27-46. [pdf]
    • Yao, W. (2010). A Profile Likelihood Method for Normal Mixture with Unequal Variance. Journal of Statistical Planning and Inference, 140, 2089-2098. [pdf], Matlab code.
    • Yao, W. and Lindsay, B. G. (2009). Bayesian Mixture Labeling by Highest Posterior Density. Journal of American Statistical Association, 104, 758-767. [pdf], Matlab code.