Add to ORKGIn this paper, two types of kernel based estimators of hazard rate under left truncation and right censorship are considered. An asymptotic representation of the integrated squared error for both estimators is obtained. Also it is shown that the bandwidth selected by the data-based method of least squares cross-validation is asymptotically optimal in a compelling sense.Left truncation right censorship Hazard rate estimation Asymptotic representation Cross-validation Optimal bandwidth
Kernel density estimator, right censorship, strong convergence, hazard rate estimator,
We study an estimator of the survival function under the random censoring model. Bahadur-type repres...
This paper develops a consistent test for the correct hazard rate specification within the context o...
In this paper, two types of kernel based estimators of hazard rate under left truncation and right c...
SUMMARY: Left truncation and right censoring arise frequently in practice for life data. This paper ...
Let X be the variable of interest with distribution function F, hazard function $\lambda$ and Y be a...
In this paper, the proposed estimator for the unknown nonparametric regression function is a Nadarya...
In this thesis, we are concerned with the asymptotic properties of kernel estimates with variable ba...
Nonparametric kernel estimators for hazard functions and their derivatives are considered under the ...
The nonparametric estimation for the density and hazard rate functions for right-censored data using...
This note presents an estimator of the hazard rate function based on right censored data. A collecti...
An asymptotic representation of the mean weighted integrated squared error for the kernel based esti...
In this paper, we study a smooth estimator of the conditional hazard rate function in the censorship...
AbstractThe data consists of multivariate failure times under right random censorship. By the kernel...
We suggest a completely empirical approach to the construction of confidence bands for hazard functi...
Kernel density estimator, right censorship, strong convergence, hazard rate estimator,
We study an estimator of the survival function under the random censoring model. Bahadur-type repres...
This paper develops a consistent test for the correct hazard rate specification within the context o...
In this paper, two types of kernel based estimators of hazard rate under left truncation and right c...
SUMMARY: Left truncation and right censoring arise frequently in practice for life data. This paper ...
Let X be the variable of interest with distribution function F, hazard function $\lambda$ and Y be a...
In this paper, the proposed estimator for the unknown nonparametric regression function is a Nadarya...
In this thesis, we are concerned with the asymptotic properties of kernel estimates with variable ba...
Nonparametric kernel estimators for hazard functions and their derivatives are considered under the ...
The nonparametric estimation for the density and hazard rate functions for right-censored data using...
This note presents an estimator of the hazard rate function based on right censored data. A collecti...
An asymptotic representation of the mean weighted integrated squared error for the kernel based esti...
In this paper, we study a smooth estimator of the conditional hazard rate function in the censorship...
AbstractThe data consists of multivariate failure times under right random censorship. By the kernel...
We suggest a completely empirical approach to the construction of confidence bands for hazard functi...
Kernel density estimator, right censorship, strong convergence, hazard rate estimator,
We study an estimator of the survival function under the random censoring model. Bahadur-type repres...
This paper develops a consistent test for the correct hazard rate specification within the context o...