Adaptive estimation for varying coefficient models

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...

Efficient Estimation in Heteroscedastic Varying Coefficient Models

This paper considers statistical inference for the heteroscedastic varying coefficient model. We propose an efficient estimator for coefficient functions that is more efficient than the conventional local-linear estimator. We establish asymptotic normality for the proposed estimator and conduct some simulation to illustrate the performance of the proposed method.

Adaptive LASSO for Varying-Coefficient Partially Linear Measurement Error Models

This paper extends the adaptive LASSO (ALASSO) for simultaneous parameter estimation and variable selection to a varying-coefficient partially linear model where some of the covariates are subject to measurement errors of an additive form. We draw comparisons with the SCAD, and prove that both the ALASSO and SCAD attain the oracle property under this setup. We further develop an algorithm in th...

Efficient estimation and inferences for varying-coefficient models

Generalized Varying-Coefficient Models

This paper deals with statistical inferences based on the generalized varying-coeÆcient models proposed by Hastie and Tibshirani (1993). Local polynomial regression techniques are used to estimate coeÆcient functions and the asymptotic normality of the resulting estimators is established. The standard error formulas for estimated coeÆcients are derived and are empirically tested. A goodness-oft...