All Stories

  1. A Cholesky-based estimation for large-dimensional covariance matrices

    Article • Journal of Applied Statistics, September 2019, Taylor & Francis

    Mingqiu Wang, Xiaoning Kang

  2. SCAD-Penalized Least Absolute Deviation Regression in High-Dimensional Models

    Article • Communication in Statistics- Theory and Methods, October 2014, Taylor & Francis

    Mingqiu Wang, Dr Guo-Liang TIAN

  3. Quadratic Approximation via the SCAD Penalty with a Diverging Number of Parameters

    Article • Communications in Statistics - Simulation and Computation, June 2014, Taylor & Francis

    Mingqiu Wang

  4. Adaptive Lasso estimators for ultrahigh dimensional generalized linear models

    Article • Statistics & Probability Letters, June 2014, Elsevier

    Mingqiu Wang

  5. A note on the one-step estimator for ultrahigh dimensionality

    Article • Journal of Computational and Applied Mathematics, April 2014, Elsevier

    Mingqiu Wang

  6. Combined-penalized likelihood estimations with a diverging number of parameters

    Article • Journal of Applied Statistics, December 2013, Taylor & Francis

    Mingqiu Wang

  7. Variable selection in the high-dimensional continuous generalized linear model with current status data

    Article • Journal of Applied Statistics, September 2013, Taylor & Francis

    Mingqiu Wang, Dr Guo-Liang TIAN

  8. Identification for semiparametric varying coefficient partially linear models

    Article • Statistics & Probability Letters, May 2013, Elsevier

    Mingqiu Wang

  9. Bridge Estimators in the Partially Linear Model with High Dimensionality

    Article • Communication in Statistics- Theory and Methods, December 2011, Taylor & Francis

    Mingqiu Wang

  10. Bridge estimation for generalized linear models with a diverging number of parameters

    Article • Statistics & Probability Letters, November 2010, Elsevier

    Mingqiu Wang