In this paper, we introduce a family of robust statistics which allow to decide between a parametric model and a semiparametric one. More precisely, under a generalized partially linear model, i.e., when the observations satisfy View the MathML source with View the MathML source and H a known link function, we want to test H0:η(t)=α+γt against H1:η is a nonlinear smooth function. A general approach which includes robust estimators based on a robustified deviance or a robustified quasi-likelihood is considered. The asymptotic behavior of the test statistic under the null hypothesis is obtained.Fil: Boente Boente, Graciela Lina. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigacion...
By starting from a natural class of robust estimators for generalized linear models based on the not...
Partially linear models are important tools in statistical modelling, combining the flexibility of n...
In many situations, data follow a generalized linear model in which the mean of the responses is mo...
In this paper, we introduce a family of robust statistics which allow to decide between a parametri...
In many situations, data follow a generalized partly linear model in which the mean of the responses...
This paper focuses on the problem of testing the null hypothesis H0β: β = βo and H0g: g = go, under ...
We consider a generalized partially linear model E(Y|X,T) = G{X'b + m(T)} where G is a known functio...
We consider robust testing on the regression parameter of a partially linear regression model, where...
A natural generalization of the well known generalized linear models is to allow only for some of th...
En esta tesis, introducimos una nueva clase de estimadores robustos para las componentes paramétrica...
AbstractIn the framework of generalized linear models, the nonrobustness of classical estimators and...
Generalized linear models are often misspecified because of overdispersion, heteroscedasticity and i...
By approximating the nonparametric component using a regression spline in generalized partial linear...
In the framework of generalized linear models, the nonrobustness of classical estimators and tests f...
By starting from a natural class of robust estimators for generalized linear models based on the not...
By starting from a natural class of robust estimators for generalized linear models based on the not...
Partially linear models are important tools in statistical modelling, combining the flexibility of n...
In many situations, data follow a generalized linear model in which the mean of the responses is mo...
In this paper, we introduce a family of robust statistics which allow to decide between a parametri...
In many situations, data follow a generalized partly linear model in which the mean of the responses...
This paper focuses on the problem of testing the null hypothesis H0β: β = βo and H0g: g = go, under ...
We consider a generalized partially linear model E(Y|X,T) = G{X'b + m(T)} where G is a known functio...
We consider robust testing on the regression parameter of a partially linear regression model, where...
A natural generalization of the well known generalized linear models is to allow only for some of th...
En esta tesis, introducimos una nueva clase de estimadores robustos para las componentes paramétrica...
AbstractIn the framework of generalized linear models, the nonrobustness of classical estimators and...
Generalized linear models are often misspecified because of overdispersion, heteroscedasticity and i...
By approximating the nonparametric component using a regression spline in generalized partial linear...
In the framework of generalized linear models, the nonrobustness of classical estimators and tests f...
By starting from a natural class of robust estimators for generalized linear models based on the not...
By starting from a natural class of robust estimators for generalized linear models based on the not...
Partially linear models are important tools in statistical modelling, combining the flexibility of n...
In many situations, data follow a generalized linear model in which the mean of the responses is mo...