USA For the class of single-index models, I construct a semiparametric estimator of coefficients up to a multiplicative constant that exhibits l/x- n consistency and asymptotic normality. This class of models includes censored and truncated Tobit models, binary choice models, and duration models with unobserved individual heterogeneity and random censoring. I also investigate a weighting scheme that achieves the semiparametric efficiency bound. 1
We consider a semiparametric single-index model and suppose that endogeneity is present in the expla...
In partially linear single-index models, we obtain the semiparametrically efficient profile least-sq...
Many well-known rank tests can be viewed as score tests under probabilistic index models (PIMs), tha...
For the class of single-index models, I construct a semiparametric estimator of coefficients up to ...
AbstractThis paper proposes a method for estimation of a class of partially linear single-index mode...
AbstractThe censored single-index model provides a flexible way for modelling the association betwee...
[[abstract]]This paper proposes a method for estimation of a class of partially linear single-index ...
Two Essays on Single-index Models Single-index models, in the simplest form E(y|x) = g(xTb), genera...
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 ...
Single-index models are popular regression models that are more flexible than linear models and stil...
This research develops semiparametric kernel-based estimators of state-speci¯c conditional transitio...
AbstractIn this note, we revisit the single-index model with heteroscedastic error, and recommend an...
This paper proposes a semiparametric estimator for single- and multiple index models.It provides an ...
AbstractConsider a varying-coefficient single-index model which consists of two parts: the linear pa...
We consider a semiparametric single-index model and suppose that endogeneity is present in the expla...
In partially linear single-index models, we obtain the semiparametrically efficient profile least-sq...
Many well-known rank tests can be viewed as score tests under probabilistic index models (PIMs), tha...
For the class of single-index models, I construct a semiparametric estimator of coefficients up to ...
AbstractThis paper proposes a method for estimation of a class of partially linear single-index mode...
AbstractThe censored single-index model provides a flexible way for modelling the association betwee...
[[abstract]]This paper proposes a method for estimation of a class of partially linear single-index ...
Two Essays on Single-index Models Single-index models, in the simplest form E(y|x) = g(xTb), genera...
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 ...
Single-index models are popular regression models that are more flexible than linear models and stil...
This research develops semiparametric kernel-based estimators of state-speci¯c conditional transitio...
AbstractIn this note, we revisit the single-index model with heteroscedastic error, and recommend an...
This paper proposes a semiparametric estimator for single- and multiple index models.It provides an ...
AbstractConsider a varying-coefficient single-index model which consists of two parts: the linear pa...
We consider a semiparametric single-index model and suppose that endogeneity is present in the expla...
In partially linear single-index models, we obtain the semiparametrically efficient profile least-sq...
Many well-known rank tests can be viewed as score tests under probabilistic index models (PIMs), tha...