Non-linear relationships are accommodated in a regression model using smoothing functions. Interaction may occurs between continuous variable, in this case interaction between nonlinear and linear covariate leads to varying coefficent model (VCM), a subclass of generalized additive model. Additive models can be estimated as generalized linear mixed models, after being reparametrized. In this article we show three different type of matrix design for mixed model for VCM, by applying b-spline smoothing functions. An application on real data is provided and model estimates re computed with a Bayesian approach
Spline smoothing is a popular method of estimating the functions in a nonparametric regression model...
Semiparametric regression offers a flexible framework for modeling nonlinear relationships between a...
In statistics, linear modelling techniques are widely used methods to explain one variable by others...
Varying-coefficient models provide a flexible framework for semi- and nonparametric generalized regr...
With the emergence of semi- and nonparametric regression the generalized linear mixed model has been...
Summary. Generalized additive mixed models are proposed for overdispersed and correlated data, which...
We present a novel method for the estimation of variance parameters in generalised linear mixed mode...
Nonparametric regression models continue to receive more attention and appreciation with the advance...
We present a novel method for the estimation of variance parameters in generalised linear mixed mode...
Regression models describingthe dependence between a univariate response and a set of covariates pla...
Generalized additive models (GAM) for modelling nonlinear effects of continuous covariates are now w...
We survey and compare model-based approaches to regression for cross-sectional and longitudinal data...
Generalized additive mixed models extend the common parametric predictor of generalized linear model...
AbstractThe mixed model of analysis of variance is a linear model in which some terms that would oth...
Spline smoothing is a popular method of estimating the functions in a nonparametric regression model...
Semiparametric regression offers a flexible framework for modeling nonlinear relationships between a...
In statistics, linear modelling techniques are widely used methods to explain one variable by others...
Varying-coefficient models provide a flexible framework for semi- and nonparametric generalized regr...
With the emergence of semi- and nonparametric regression the generalized linear mixed model has been...
Summary. Generalized additive mixed models are proposed for overdispersed and correlated data, which...
We present a novel method for the estimation of variance parameters in generalised linear mixed mode...
Nonparametric regression models continue to receive more attention and appreciation with the advance...
We present a novel method for the estimation of variance parameters in generalised linear mixed mode...
Regression models describingthe dependence between a univariate response and a set of covariates pla...
Generalized additive models (GAM) for modelling nonlinear effects of continuous covariates are now w...
We survey and compare model-based approaches to regression for cross-sectional and longitudinal data...
Generalized additive mixed models extend the common parametric predictor of generalized linear model...
AbstractThe mixed model of analysis of variance is a linear model in which some terms that would oth...
Spline smoothing is a popular method of estimating the functions in a nonparametric regression model...
Semiparametric regression offers a flexible framework for modeling nonlinear relationships between a...
In statistics, linear modelling techniques are widely used methods to explain one variable by others...