主 题：Estimation for bivariate quantile varying coefficient model
内容简介：We propose a bivariate quantile regression method for the bivariate varying coefficient model through a directional approach. The varying coefficients are approximated by the B-spline basis and an L2-type penalty is imposed to achieve desired smoothness. We develop a multistage estimation procedure based on the Propagation-Separation (PS) approach to borrow information from nearby directions. The PS method is capable of handling the computational complexity raised by simultaneously considering multiple directions to efficiently estimate varying coefficients while guaranteeing certain smoothness along directions. We reformulate the optimization problem and solve it by the Alternating Direction Method of Multipliers (ADMM), which is implemented using R while the core is written in C to
speed it up. Simulation studies are conducted to confirm the finite sample performance of our proposed method. A real data on Diffusion Tensor Imaging (DTI) properties from a clinical study on neurodevelopment is analyzed. Joint work with Haoxu Shu, Qianchuan Chad He, Giseon Heo, John
Gilmore, and Hongtu Zhu.
报告人：Linglong Kong 博导
时 间：2016-12-23 09:00
举办单位：理学院 统计学与大数据研究院 科研部