Add to ORKGIn this article, estimation methods of the semiparametric generalized linear model known as the generalized partial linear model (GPLM) are reviewed. These methods are based on using kernel smoothing functions in the estimation of the nonparametric component of the model. We derive the algorithms for the estimation process and develop these algorithms for the generalized partial linear model (GPLM) with a binary response
By approximating the nonparametric component using a regression spline in generalized partial linear...
The generalized linear model (Nelder & Wedderburn, 1972) has become an elegant and practical opt...
This paper describes a class of heteroscedastic generalized linear regression models in which a subs...
A particular semiparametric model of interest is the generalized partial linear model (GPLM) which a...
A particular semiparametric model of interest is the generalized partial linear model GPLM which al...
We study generalized additive partial linear models, proposing the use of polynomial spline smoothin...
In this article we consider robust generalized estimating equations for the analysis of semiparametr...
In this article, we propose to estimate the regression parameters in a semiparametric generalized li...
This paper is concerned with semiparametric efficient estimation of a generalized partially linear v...
The typical generalized linear model for a regression of a response Y on predictors (X, Z) has condi...
AbstractIn this paper, we consider robust generalized estimating equations for the analysis of semip...
In regression studies, semi-parametric models provide both flexibility and interpretability. In this...
We consider a generalized partially linear model E(Y|X,T) = G{X'b + m(T)} where G is a known functio...
One of the most di±cult problems in applications of semiparametric generalized par-tially linear sin...
summary:The paper investigates generalized linear models (GLM's) with binary responses such as the l...
By approximating the nonparametric component using a regression spline in generalized partial linear...
The generalized linear model (Nelder & Wedderburn, 1972) has become an elegant and practical opt...
This paper describes a class of heteroscedastic generalized linear regression models in which a subs...
A particular semiparametric model of interest is the generalized partial linear model (GPLM) which a...
A particular semiparametric model of interest is the generalized partial linear model GPLM which al...
We study generalized additive partial linear models, proposing the use of polynomial spline smoothin...
In this article we consider robust generalized estimating equations for the analysis of semiparametr...
In this article, we propose to estimate the regression parameters in a semiparametric generalized li...
This paper is concerned with semiparametric efficient estimation of a generalized partially linear v...
The typical generalized linear model for a regression of a response Y on predictors (X, Z) has condi...
AbstractIn this paper, we consider robust generalized estimating equations for the analysis of semip...
In regression studies, semi-parametric models provide both flexibility and interpretability. In this...
We consider a generalized partially linear model E(Y|X,T) = G{X'b + m(T)} where G is a known functio...
One of the most di±cult problems in applications of semiparametric generalized par-tially linear sin...
summary:The paper investigates generalized linear models (GLM's) with binary responses such as the l...
By approximating the nonparametric component using a regression spline in generalized partial linear...
The generalized linear model (Nelder & Wedderburn, 1972) has become an elegant and practical opt...
This paper describes a class of heteroscedastic generalized linear regression models in which a subs...