We develop change-point methodology for identifying dynamic trends in the scale and shape parameters of a Weibull distribution. The methodology includes asymptotics of the likelihood ratio statistic for detecting unknown changes in the parameters as well as asymptotics of the maximum likelihood esti
Method of medians for lifetime data with Weibull models
β Scribed by Xuming He; Wing K. Fung
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 149 KB
- Volume
- 18
- Category
- Article
- ISSN
- 0277-6715
No coin nor oath required. For personal study only.
β¦ Synopsis
The Weibull family of distributions is frequently used in failure time models. The maximum likelihood estimator is very sensitive to occurrence of upper and lower outliers, especially when the hazard function is increasing. We consider the method of medians estimator for the two-parameter Weibull model. As an M-estimator, it has a bounded in#uence function and is highly robust against outliers. It is easy to compute as it requires solving only one equation instead of a pair of equations as for most other M-estimators. Furthermore, no assumptions or adjustments are needed for the estimator when there are some possibly censored observations at either end of the sample. About 16 per cent of the largest observations and 34 per cent of the smallest observations may be censored without a!ecting the calculations. We also present a simple criterion to choose between the maximum likelihood estimator and the method of medians estimator to improve on the "nite-sample e$ciency of the Weibull model. Robust inference on the shape parameter is also considered. The usefulness with contaminated or censored samples is illustrated by examples on three lifetime data sets. A simulation study was carried out to assess the performance of the proposed estimator and the con"dence intervals of a variety of contaminated Weibull models.
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