TY  - INPR
A1  - Liero, Hannelore
T1  - Testing the Hazard Rate, Part I
N2  - We consider a nonparametric survival model with random censoring. To test whether the hazard rate has a parametric form the unknown hazard rate is estimated by a kernel estimator. Based on a limit theorem stating the asymptotic normality of the quadratic distance of this estimator from the smoothed hypothesis an asymptotic ®-test is proposed. Since the test statistic depends on the maximum likelihood estimator for the unknown parameter in the hypothetical model properties of this parameter estimator are investigated. Power considerations complete the approach.
T3  - Mathematische Statistik und Wahrscheinlichkeitstheorie : Preprint - 2003, 17 
KW  - kernel estimator of the hazard rate
KW  - goodness of fit
KW  - maximum likelihood estimator
KW  - limit theorem for integrated squared difference
KW  - censoring
Y1  - 2011
UR  - https://publishup.uni-potsdam.de/frontdoor/index/index/docId/4868
UR  - https://nbn-resolving.org/urn:nbn:de:kobv:517-opus-51510
ER  -