Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Entire DC Network
Density Estimation For Lifetime Distributions Under Semi-Parametric Random Censorship Models, Carsten Harlass
Density Estimation For Lifetime Distributions Under Semi-Parametric Random Censorship Models, Carsten Harlass
Theses and Dissertations
We derive product limit estimators of survival times and failure rates for randomly right censored data as the numerical solution of identifying Volterra integral equations by employing explicit and implicit Euler schemes. While the first approach results in some known estimators, the latter leads to a new general type of product limit estimator. Plugging in established methods to approximate the conditional probability of the censoring indicator given the observation, we introduce new semi-parametric and presmoothed Kaplan-Meier type estimators. In the case of the semi-parametric random censorship model, i.e. the latter probability belonging to some parametric family, we study the strong …
Semiparametric Estimation Of The Survival Function In The Presence Of Covariates, Madlen Gebauer
Semiparametric Estimation Of The Survival Function In The Presence Of Covariates, Madlen Gebauer
Theses and Dissertations
The main interest of survival analysis is to estimate the distribution function of the survival time based on observations of a random sample. In this thesis, a semiparametric estimator is used not only to estimate the survival probability, but also to consider the influence of explanatory variables within the estimation. Therefore, the weighted maximum likelihood estimator of the conditional survival function is derived and a corresponding pointwise likelihood ratio confidence band is developed. Subsequently, the established estimator is compared to a similar estimator which was proposed by Iglesias-Pérez and de Ũna-Álvarez (2008). Since the idea of this paper arose in …