Model selection
Bayesian forecasting and dynamic models (2nd ed.)
Bayesian forecasting and dynamic models (2nd ed.)
Variable bandwidth selection in varying-coefficient models
Journal of Multivariate Analysis
Estimation of a semiparametric varying-coefficient partially linear errors-in-variables model
Journal of Multivariate Analysis
Varying-coefficient single-index model
Computational Statistics & Data Analysis
Estimation in covariate-adjusted regression
Computational Statistics & Data Analysis
Simultaneous confidence band and hypothesis test in generalised varying-coefficient models
Journal of Multivariate Analysis
Journal of Multivariate Analysis
Semiparametric likelihood estimation in survival models with informative censoring
Journal of Multivariate Analysis
Parametric component detection and variable selection in varying-coefficient partially linear models
Journal of Multivariate Analysis
Computational Statistics & Data Analysis
Estimation and inference of semi-varying coefficient models with heteroscedastic errors
Journal of Multivariate Analysis
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Varying coefficient models are useful extensions of the classical linear models. Under the condition that the coefficient functions possess about the same degrees of smoothness, the model can easily be estimated via simple local regression. This leads to the one-step estimation procedure. In this paper, we consider a semivarying coefficient model which is an extension of the varying coefficient model, which is called the semivarying-coefficient model. Procedures for estimation of the linear part and the nonparametric part are developed and their associated statistical properties are studied. The proposed methods are illustrated by some simulation studies and a real example.