Varying coefficient models are a useful extension of classical linear models. They arise
naturally when one wishes to examine how regression coefficients change over different …

This article deals with statistical inferences based on the varying-coefficient models
proposed by Hastie and Tibshirani. Local polynomial regression techniques are used to …

A global smoothing procedure is developed using basis function approximations for
estimating the parameters of a varying‐coefficient model with repeated measurements …

Varying-coefficient linear models arise from multivariate nonparametric regression, non-
linear time series modelling and forecasting, functional data analysis, longitudinal data …

Varying coefficient regression models are known to be very useful tools for analysing the
relation between a response and a group of covariates. Their structure and interpretability …

Intuition suggests that altering the covariance structure of a parametric model for repeated-
measures data alters the variances of the model's estimated mean parameters. The purpose …

The varying coefficient models are very important tool to explore the dynamic pattern in
many scientific areas, such as economics, finance, politics, epidemiology, medical science …

Nonparametric varying-coefficient models are commonly used for analyzing data measured
repeatedly over time, including longitudinal and functional response data. Although many …

Very early on in the development of methods for the analysis of time series and the
relationships between time series, it was recognized that techniques based upon constant …

This paper deals with the estimation of conditional quantiles in varying coefficient models by
estimating the coefficients. Varying coefficient models are among popular models that have …