• Title of article

    Non-parametric shrinkage mean estimation for quadratic loss functions with unknown covariance matrices

  • Author/Authors

    Wang، نويسنده , , Cheng-Li Tong، نويسنده , , Tiejun and Cao، نويسنده , , Longbing and Miao، نويسنده , , Baiqi، نويسنده ,

  • Issue Information
    دوفصلنامه با شماره پیاپی سال 2014
  • Pages
    11
  • From page
    222
  • To page
    232
  • Abstract
    In this paper, a shrinkage estimator for the population mean is proposed under known quadratic loss functions with unknown covariance matrices. The new estimator is non-parametric in the sense that it does not assume a specific parametric distribution for the data and it does not require the prior information on the population covariance matrix. Analytical results on the improvement of the proposed shrinkage estimator are provided and some corresponding asymptotic properties are also derived. Finally, we demonstrate the practical improvement of the proposed method over existing methods through extensive simulation studies and real data analysis.
  • Keywords
    High-dimensional data , Shrinkage estimator , Large p small n , U -statistic
  • Journal title
    Journal of Multivariate Analysis
  • Serial Year
    2014
  • Journal title
    Journal of Multivariate Analysis
  • Record number

    1566645