Testing the Hazard Rate, Part I
- 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.
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| Author details: | Hannelore Liero |
|---|---|
| URN: | urn:nbn:de:kobv:517-opus-51510 |
| Publication series (Volume number): | Mathematische Statistik und Wahrscheinlichkeitstheorie : Preprint (2003, 17) |
| Publication type: | Preprint |
| Language: | English |
| Publication year: | 2003 |
| Publishing institution: | Universität Potsdam |
| Release date: | 2011/03/28 |
| Tag: | censoring; goodness of fit; kernel estimator of the hazard rate; limit theorem for integrated squared difference; maximum likelihood estimator |
| RVK - Regensburg classification: | SI 990 |
| Organizational units: | Mathematisch-Naturwissenschaftliche Fakultät / Institut für Mathematik |
| DDC classification: | 5 Naturwissenschaften und Mathematik / 51 Mathematik / 510 Mathematik |
| License (German): |  Keine öffentliche Lizenz: Unter Urheberrechtsschutz |
