Bayes factors for accelerated life testing models
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arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2021
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| Acceso en línea: | |
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| _version_ | 1866909991073480704 |
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| author | Smit, Neill Raubenheimer, Lizanne |
| author_facet | Smit, Neill Raubenheimer, Lizanne |
| contents | In Bayesian accelerated life testing, the most used tool for model comparison is the deviance information criterion. An alternative and more formal approach is to use Bayes factors to compare models. However, Bayesian accelerated life testing models with more than one stressor often have mathematically intractable posterior distributions and Markov chain Monte Carlo methods are employed to obtain posterior samples to base inference on. The computation of the marginal likelihood is challenging when working with such complex models. In this paper, methods for approximating the marginal likelihood and the application thereof in the accelerated life testing paradigm are explored for dual-stress models. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2111_09593 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | Bayes factors for accelerated life testing models Smit, Neill Raubenheimer, Lizanne Methodology Applications 62F15 G.3 In Bayesian accelerated life testing, the most used tool for model comparison is the deviance information criterion. An alternative and more formal approach is to use Bayes factors to compare models. However, Bayesian accelerated life testing models with more than one stressor often have mathematically intractable posterior distributions and Markov chain Monte Carlo methods are employed to obtain posterior samples to base inference on. The computation of the marginal likelihood is challenging when working with such complex models. In this paper, methods for approximating the marginal likelihood and the application thereof in the accelerated life testing paradigm are explored for dual-stress models. |
| title | Bayes factors for accelerated life testing models |
| topic | Methodology Applications 62F15 G.3 |
| url | https://arxiv.org/abs/2111.09593 |