Varying coefficient models

Abstract

One of the most interesting forms of nonlinear regression models is the varying coefficient model (VCM). Unlike the linear regression model, VCMs were introduced by Hastie and Tibshirani (1993) to allow the regression coefficients to vary systematically and smoothly in more than one dimension. It is worth noting the distinction between the VCM and the so-called random coefficients model, which assumes that the coefficients vary non-systematically (randomly). Versions of the VCM are encountered in the literature as functional coefficient models (see Cai, Fan and Yao, 2000) and smooth coefficient models (see Li et al, 2002).KeywordsAmerican Statistical AssociationNonparametric RegressionPolynomial SplineGeneralize Likelihood Ratio TestNonlinear Time Series ModelThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.