Nonparametric estimation and testing in survival models

The aim of this paper is to demonstrate that nonparametric smoothing methods for estimating functions can be an useful tool in the analysis of life time data. After stating some basic notations we will present a data example. Applying standard parametric methods to these data we will see that this approach fails - basic features of the underlying functions are not reflected by their estimates. Our proposal is to use nonparametric estimation methods. These methods are explained in section 2. Nonparametric approaches are better in the sense that they are more flexible, and misspecifications of the model are avoided. But, parametric models have the advantage that the parameters can be interpreted. So, finally, we will formulate a test procedure to check whether a parametric or a nonparametric model is appropriate.

Metadaten
Verfasserangaben:	Henning Läuter, Hannelore Liero
URN:	urn:nbn:de:kobv:517-opus-51586
Schriftenreihe (Bandnummer):	Mathematische Statistik und Wahrscheinlichkeitstheorie : Preprint (2004, 05)
Publikationstyp:	Preprint
Sprache:	Englisch
Erscheinungsjahr:	2004
Veröffentlichende Institution:	Universität Potsdam
Datum der Freischaltung:	29.03.2011
RVK - Regensburger Verbundklassifikation:	SI 990
Organisationseinheiten:	Mathematisch-Naturwissenschaftliche Fakultät / Institut für Mathematik
DDC-Klassifikation:	5 Naturwissenschaften und Mathematik / 51 Mathematik / 510 Mathematik
Lizenz (Deutsch):	Keine öffentliche Lizenz: Unter Urheberrechtsschutz