Add to ORKGAbstract: Varying coefficient models have been widely used in longitudinal data analysis, nonlinear ...
The complexity of semiparametric models poses new challenges to sta-tistical inference and model sel...
We propose a novel varying coefficient model (VCM), called principal varying coefficient model (PVCM...
Single index varying coefficient model is a very attractive statistical model due to its ability to ...
AbstractVarying coefficient models are useful extensions of the classical linear models. Under the c...
Varying coefficient models are useful extensions of classical linear models. In practice, some of th...
Varying coefficient models are useful extensions of the classical linear models. Under the condition...
Varying coefficient models are useful extensions of classical lin- ear models. In practice, some of ...
Since the proposal of the least absolute shrinkage and selection operator (LASSO) (Tibshirani, 1996)...
In this paper, we study the model selection and structure specification for the generalised semi-var...
AbstractThis paper focuses on the variable selections for semiparametric varying coefficient partial...
Varying-coefficient linear models arise from multivariate nonparametric regression, nonlinear time s...
This paper presents a new method for estimation in semiparametric regression models, based on a mode...
10.1016/j.jspi.2008.10.009Journal of Statistical Planning and Inference13972138-2146JSPI
A partially time-varying coefficient model is introduced to characterise the nonlinearity and trendi...
Abstract: Varying coefficient models have been widely used in longitudinal data analysis, nonlinear ...
The complexity of semiparametric models poses new challenges to sta-tistical inference and model sel...
We propose a novel varying coefficient model (VCM), called principal varying coefficient model (PVCM...
Single index varying coefficient model is a very attractive statistical model due to its ability to ...
AbstractVarying coefficient models are useful extensions of the classical linear models. Under the c...
Varying coefficient models are useful extensions of classical linear models. In practice, some of th...
Varying coefficient models are useful extensions of the classical linear models. Under the condition...
Varying coefficient models are useful extensions of classical lin- ear models. In practice, some of ...
Since the proposal of the least absolute shrinkage and selection operator (LASSO) (Tibshirani, 1996)...
In this paper, we study the model selection and structure specification for the generalised semi-var...
AbstractThis paper focuses on the variable selections for semiparametric varying coefficient partial...
Varying-coefficient linear models arise from multivariate nonparametric regression, nonlinear time s...
This paper presents a new method for estimation in semiparametric regression models, based on a mode...
10.1016/j.jspi.2008.10.009Journal of Statistical Planning and Inference13972138-2146JSPI
A partially time-varying coefficient model is introduced to characterise the nonlinearity and trendi...
Abstract: Varying coefficient models have been widely used in longitudinal data analysis, nonlinear ...
The complexity of semiparametric models poses new challenges to sta-tistical inference and model sel...
We propose a novel varying coefficient model (VCM), called principal varying coefficient model (PVCM...