We consider a semi-parametric model for recurrent events. The model consists of an unknown hazard rate function, the infinite-dimensional parameter of the model, and a parametrically specified effective age function. We will present a condition on the family of effective age functions under which the profile likelihood function evaluated at the parameter vector theta, say, exceeds the profile likelihood function evaluated at the parameter vector (theta) over bar, say, with probability p. From this we derive a condition under which profile likelihood inference for the finite-dimensional parameter of the model leads to inconsistent estimates. Examples will be presented. In particular, we will provide an example where the profile likelihood fu...
Classic Estimating Equations (CEE) were first introduced by Godambe and have been widely used under ...
Interval-censored multivariate failure time data arise when there are multiple types of failure or t...
Abstract: A profile likelihood inference is made for the regression coefficient and frailty paramete...
We consider a semi-parametric model for recurrent events. The model consists of an unknown hazard ra...
International audienceWe consider a semi-parametric model for recurrent events. The model consists o...
In this thesis, we have investigated the efficiency of profile likelihood in the estimation of param...
Profile likelihood is a popular method of estimation in the presence of a nuisance parameter. It is ...
We examine a new general class of hazard rate models for duration data, containing a parametric and ...
The proportional hazards (PH) model and the accelerated failure time (AFT) model are the most popula...
We examine a new general class of hazard rate models for durationdata, containing a parametric and a...
[[abstract]]This paper describes our studies on non-parametric maximum-likelihood estimators in a se...
This paper revisits the classical inference results for profile quasi maximum likelihood estimators ...
[[abstract]]This paper describes our studies on non-parametric maximum-likelihood estimators in a se...
Varying-coefficient partially linear models are frequently used in statistical modeling. Yet, their...
We consider semiparametric models whose infinite-dimensional parameter corresponds to a probability ...
Classic Estimating Equations (CEE) were first introduced by Godambe and have been widely used under ...
Interval-censored multivariate failure time data arise when there are multiple types of failure or t...
Abstract: A profile likelihood inference is made for the regression coefficient and frailty paramete...
We consider a semi-parametric model for recurrent events. The model consists of an unknown hazard ra...
International audienceWe consider a semi-parametric model for recurrent events. The model consists o...
In this thesis, we have investigated the efficiency of profile likelihood in the estimation of param...
Profile likelihood is a popular method of estimation in the presence of a nuisance parameter. It is ...
We examine a new general class of hazard rate models for duration data, containing a parametric and ...
The proportional hazards (PH) model and the accelerated failure time (AFT) model are the most popula...
We examine a new general class of hazard rate models for durationdata, containing a parametric and a...
[[abstract]]This paper describes our studies on non-parametric maximum-likelihood estimators in a se...
This paper revisits the classical inference results for profile quasi maximum likelihood estimators ...
[[abstract]]This paper describes our studies on non-parametric maximum-likelihood estimators in a se...
Varying-coefficient partially linear models are frequently used in statistical modeling. Yet, their...
We consider semiparametric models whose infinite-dimensional parameter corresponds to a probability ...
Classic Estimating Equations (CEE) were first introduced by Godambe and have been widely used under ...
Interval-censored multivariate failure time data arise when there are multiple types of failure or t...
Abstract: A profile likelihood inference is made for the regression coefficient and frailty paramete...