Weighted Local Linear Smoothing Method for Randomly Right Censored Varying Coefficient Models

Smoothing Spline Regression Estimates for Randomly Right Censored Data

Adaptive Varying-coefficient Linear Models

Varying-coefficient linear models arise from multivariate nonparametric regression, nonlinear time series modelling and forecasting, functional data analysis, longitudinal data analysis, and others. It has been a common practice to assume that the vary-coefficients are functions of a given variable which is often called an index. A frequently asked question is which variable should be used as t...

Local Rank Inference for Varying Coefficient Models.

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 linea...

Variable Selection for Partially Linear Varying Coefficient Transformation Models with Censored Data

In this paper, we study the problem of variable selection for varying coefficient transformation models with censored data. We fit the varying coefficient transformation models by maximizing the marginal likelihood subject to a shrinkage-type penalty, which encourages sparse solutions and hence facilitates the process of variable selection. We further provide an efficient computation algorithm ...

Convergence Rates for Smoothing Spline Estimators in Varying Coefficient Models

We consider the estimation of a multiple regression model in which the coefficients change slowly in “time”, with “time” being an additional covariate. Under reasonable smoothness conditions, we prove the usual expected mean square error bounds for the smoothing spline estimators of the coefficient functions.