AbstractIn this paper we propose a cross-validation selection criterion to determine asymptotically the correct model among the family of all possible partially linear models when the underlying model is a partially linear model. We establish the asymptotic consistency of the criterion. In addition, the criterion is illustrated using two real sets of data
Recently, Hjort and Claeskens (2003) developed an asymptotic theory for model selection, model avera...
We propose and study a unified procedure for variable selection in partially linear models. A new ty...
Recently, Hjort and Claeskens (2003) developed an asymptotic theory for model selection, model avera...
In this paper we propose a cross-validation selection criterion to determine asymptotically the corr...
AbstractIn this paper we propose a cross-validation selection criterion to determine asymptotically ...
For the problem of model selection, full cross-validation has been proposed as alternative criterion...
For the problem of model selection, full cross-validation has been proposed as an alternative criter...
Model selection in nonparametric and semiparametric regression is of both theoretical and practical ...
We consider the problem of model (or variable) selection in the classical regression model based on ...
Summary For the problem of model selection full crossvalidation has been proposed as alternative c...
Estimators for the parameter of interest in semiparametric models often depend on a guessed model fo...
© 2004 Royal Statistical SocietySemiparametric time series regression is often used without checking...
It is known that semiparametric time series regression is often used without checking its suitabilit...
This thesis will consider the performance of the cross-validation copula information criterion, xv-C...
In this paper, we focus on the variable selection for semiparametric varying coefficient partially l...
Recently, Hjort and Claeskens (2003) developed an asymptotic theory for model selection, model avera...
We propose and study a unified procedure for variable selection in partially linear models. A new ty...
Recently, Hjort and Claeskens (2003) developed an asymptotic theory for model selection, model avera...
In this paper we propose a cross-validation selection criterion to determine asymptotically the corr...
AbstractIn this paper we propose a cross-validation selection criterion to determine asymptotically ...
For the problem of model selection, full cross-validation has been proposed as alternative criterion...
For the problem of model selection, full cross-validation has been proposed as an alternative criter...
Model selection in nonparametric and semiparametric regression is of both theoretical and practical ...
We consider the problem of model (or variable) selection in the classical regression model based on ...
Summary For the problem of model selection full crossvalidation has been proposed as alternative c...
Estimators for the parameter of interest in semiparametric models often depend on a guessed model fo...
© 2004 Royal Statistical SocietySemiparametric time series regression is often used without checking...
It is known that semiparametric time series regression is often used without checking its suitabilit...
This thesis will consider the performance of the cross-validation copula information criterion, xv-C...
In this paper, we focus on the variable selection for semiparametric varying coefficient partially l...
Recently, Hjort and Claeskens (2003) developed an asymptotic theory for model selection, model avera...
We propose and study a unified procedure for variable selection in partially linear models. A new ty...
Recently, Hjort and Claeskens (2003) developed an asymptotic theory for model selection, model avera...
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