Imprecise inference based on the log-rank test for accelerated life testing
| Autor: | Frank P. A. Coolen, Abdullah Ali H. Ahmadini, Tahani Coolen-Maturi |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
021103 operations research Link function 0211 other engineering and technologies Nonparametric statistics Inference 02 engineering and technology computer.software_genre 01 natural sciences Accelerated life testing Log-rank test 010104 statistics & probability Predictive inference Robustness (computer science) Data mining 0101 mathematics Statistics Probability and Uncertainty Parametric equation computer Mathematics |
| Zdroj: | Metrika, 2021, Vol.84, pp.913-925 [Peer Reviewed Journal] |
| Popis: | This paper presents an imprecise predictive inference method for accelerated life testing. The method is largely nonparametric, with a basic parametric function to link different stress levels. The log-rank test is used to provide imprecision for the link function parameter, which in turn provides robustness in the resulting lower and upper survival functions for a future observation at the normal stress level. An application using data from the literature is presented, and simulations show the performance and robustness of the method. In case of model misspecification, robustness may be achieved at the price of large imprecision, which would emphasize the need for more data or further model assumptions. |
| Databáze: | OpenAIRE |
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