In this paper, we study a smooth estimator of the conditional hazard rate function in the censorship model when the data exhibit some dependence structure. We show, under some regularity conditions, that the kernel estimator of the conditional hazard rate function suitably normalized is asymptotically normally distributed
Let X be the variable of interest with distribution function F, hazard function $\lambda$ and Y be a...
Let (X, Y) be a random vector, where Y denotes the variable of interest, possibly subject to random ...
In some long-term studies, a series of dependent and possibly truncated lifetimes may be observed. S...
In this paper, we study a smooth estimator of the conditional hazard rate function in the censorship...
AbstractIn some long term studies, a series of dependent and possibly censored failure times may be ...
This paper develops a consistent test for the correct hazard rate specification within the context o...
Consider a regression model in which the responses are subject to random right censoring. In this mo...
AbstractThe data consists of multivariate failure times under right random censorship. By the kernel...
We consider kernel estimation of bivariate hazard, density and conditional covariance rate function ...
The nonparametric estimation for the density and hazard rate functions for right-censored data using...
In this thesis, we are concerned with the asymptotic properties of kernel estimates with variable ba...
This note presents an estimator of the hazard rate function based on right censored data. A collecti...
Kernel density estimator, right censorship, strong convergence, hazard rate estimator,
The main goal of this paper is to study the asymptotic normality of the estimate of the Conditional ...
In this paper, two types of kernel based estimators of hazard rate under left truncation and right c...
Let X be the variable of interest with distribution function F, hazard function $\lambda$ and Y be a...
Let (X, Y) be a random vector, where Y denotes the variable of interest, possibly subject to random ...
In some long-term studies, a series of dependent and possibly truncated lifetimes may be observed. S...
In this paper, we study a smooth estimator of the conditional hazard rate function in the censorship...
AbstractIn some long term studies, a series of dependent and possibly censored failure times may be ...
This paper develops a consistent test for the correct hazard rate specification within the context o...
Consider a regression model in which the responses are subject to random right censoring. In this mo...
AbstractThe data consists of multivariate failure times under right random censorship. By the kernel...
We consider kernel estimation of bivariate hazard, density and conditional covariance rate function ...
The nonparametric estimation for the density and hazard rate functions for right-censored data using...
In this thesis, we are concerned with the asymptotic properties of kernel estimates with variable ba...
This note presents an estimator of the hazard rate function based on right censored data. A collecti...
Kernel density estimator, right censorship, strong convergence, hazard rate estimator,
The main goal of this paper is to study the asymptotic normality of the estimate of the Conditional ...
In this paper, two types of kernel based estimators of hazard rate under left truncation and right c...
Let X be the variable of interest with distribution function F, hazard function $\lambda$ and Y be a...
Let (X, Y) be a random vector, where Y denotes the variable of interest, possibly subject to random ...
In some long-term studies, a series of dependent and possibly truncated lifetimes may be observed. S...