Add to ORKGThis article is concerned with simple semiparametric alternatives to the fully parametric model (1) which allow for such curvature, but yet retain the ease of interpretation of parameters such as ff 0 and fi 0 . In this particular example, our generalization consists of two parts: (a) the linear combination f
We perform inference for the sparse and potentially high-dimensional parametric part of a partially ...
© 2014 Royal Statistical Society. We consider heteroscedastic regression models where the mean funct...
Partial linear models, a family of popular semiparametric models, provide us with an interpretable a...
The typical generalized linear model for a regression of a response Y on predictors (X, Z) has condi...
A natural generalization of the well known generalized linear models is to allow only for some of th...
Aiming to explore the relation between the response y and the stochastic explanatory vector variable...
Summary Most dimension reduction models are suited for continuous but not for discrete covariates. A...
Two Essays on Single-index Models Single-index models, in the simplest form E(y|x) = g(xTb), genera...
We study the non-parametric estimation of partially linear generalized single-index functional model...
One of the most di±cult problems in applications of semiparametric generalized partially linear sing...
In this paper, we study the estimation for a partial-linear single-index model. A two-stage estimati...
One of the most di±cult problems in applications of semiparametric generalized par-tially linear sin...
Partial dimension reduction is a general method to seek informative convex combinations of predictor...
The partially linear single-index model is a semiparametric model proposed to the case when some pre...
Generalized single-index models are natural extensions of linear models and circumvent the so-called...
We perform inference for the sparse and potentially high-dimensional parametric part of a partially ...
© 2014 Royal Statistical Society. We consider heteroscedastic regression models where the mean funct...
Partial linear models, a family of popular semiparametric models, provide us with an interpretable a...
The typical generalized linear model for a regression of a response Y on predictors (X, Z) has condi...
A natural generalization of the well known generalized linear models is to allow only for some of th...
Aiming to explore the relation between the response y and the stochastic explanatory vector variable...
Summary Most dimension reduction models are suited for continuous but not for discrete covariates. A...
Two Essays on Single-index Models Single-index models, in the simplest form E(y|x) = g(xTb), genera...
We study the non-parametric estimation of partially linear generalized single-index functional model...
One of the most di±cult problems in applications of semiparametric generalized partially linear sing...
In this paper, we study the estimation for a partial-linear single-index model. A two-stage estimati...
One of the most di±cult problems in applications of semiparametric generalized par-tially linear sin...
Partial dimension reduction is a general method to seek informative convex combinations of predictor...
The partially linear single-index model is a semiparametric model proposed to the case when some pre...
Generalized single-index models are natural extensions of linear models and circumvent the so-called...
We perform inference for the sparse and potentially high-dimensional parametric part of a partially ...
© 2014 Royal Statistical Society. We consider heteroscedastic regression models where the mean funct...
Partial linear models, a family of popular semiparametric models, provide us with an interpretable a...