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  • 统计与管理学院2017年学术报告第55

     

    【主  题】Efficient estimation of the nonparametric mean and covariance functions for longitudinal and sparse functional data

    【报告人】林华珍

    西南财经大学统计学院教授、博导,统计研究中心主任。教育部长江学者特聘教授、国家杰出青年科学基金获得者、教育部新世纪优秀人才

    【时  间】2017年8月18日(星期五)16:05-16:50

    【地  点】上海财经大学统计与管理学院大楼1316室

    【摘 要】We consider the estimation of mean and covariance functions for longitudinal and sparse functional data by  using the full quasi-likelihood coupling a modification of the local kernel smoothing method. The proposed estimators are shown to be consistent, asymptotically normal, and semiparametrically efficient in terms of their linear functionals. Their superiority to the competitors is further illustrated numerically through simulation studies. The method is applied to analyze  AIDS study and atmospheric study.

    *Joint work with Ling Zhou and Hua Liang