The problem of estimating the distribution of a lifetime when data may be leftor right censored is considered. Two models are introduced and the correspondingproduct-limit estimators are derived. Strong uniform convergence and asymptoticnormality are proved for the product-limit estimators on...

In this paper we analyze a large class of semiparametric M¡estimators for single-index models, including semiparametric quasi-likelihood and semiparametric maximumlikelihood estimators. Some possible applications to robustness are also mentioned. Thede¯nition of these estimators involves a...

We propose a two-step semiparametric pseudo-maximum likelihood procedure forsingle-index regression models where the conditional variance is a known function of theregression and an additional parameter. The Poisson single-index regression model withmultiplicative unobserved heterogeneity is an...

For tests based on nonparametric methods, power crucially depends on the dimension of theconditioning variables, and specifically decreases with this dimension. This is known as the“curse of dimensionality." We propose a new general approach to nonparametric testing inhigh dimensional settings...

We develop a novel approach to build consistent checks of parametric re-gression models when many regressors are present, based on a class of richenough semiparametric alternatives, namely single-index models. We proposean omnibus test based on the kernel method that performs against a...

The problem of estimating a nonlinear regression model when the dependent variableis randomly censored is considered. The parameter of the model is estimated by leastsquares using synthetic data, that is a suitable transformation of the response variablesthat preserves the conditional...

The problem of building bootstrap con¯dence intervals for small probabilitieswith count data is considered. The true probability distribution generating the in-dependent observations is supposed to be a mixture of a given family of power seriesdistributions. The mixing distribution is estimated...

A model for competing (resp. complementary) risks survival data where the failure time can beleft (resp. right) censored is proposed. Product-limit estimators for the survival functions of theindividual risks are derived. We deduce the strong convergence of our estimators on the wholereal...

We develop two kernel smoothing based tests of a parametric mean-regressionmodel against a nonparametric alternative when the response variable is right-censored. The new test statistics are inspired by the synthetic data and the weightedleast squares approaches for estimating the parameters of...