Local Rank Inference for Varying Coefficient Models.

ABSTRACT: By allowing the regression coefficients to change with certain covariates, the class of varying coefficient models offers a flexible approach to modeling nonlinearity and interactions between covariates. This paper proposes a novel estimation procedure for the varying coefficient models based on local ranks. The new procedure provides a highly efficient and robust alternative to the local linear least squares method, and can be conveniently implemented using existing R software package. Theoretical analysis and numerical simulations both reveal that the gain of the local rank estimator over the local linear least squares estimator, measured by the asymptotic mean squared error or the asymptotic mean integrated squared error, can be substantial. In the normal error case, the asymptotic rela

SUBMITTER: Wang L 

PROVIDER: S-EPMC2908045 | biostudies-literature | 2009 Dec

REPOSITORIES: biostudies-literature