Sampling and Bayes' Inference in Scientific Modelling and Robustness
Scientific learning is an iterative process employing Criticism and Estimation. Correspondingly the formulated model factors into two complementary parts--a predictive part allowing model criticism, and a Bayes posterior part allowing estimation. Implications for significance tests, the theory of pr...
| Veröffentlicht in: | Journal of the Royal Statistical Society. Series A (General). - Royal Statistical Society, 1948. - 143(1980), 4, Seite 383-430 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
1980
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| Zugriff auf das übergeordnete Werk: | Journal of the Royal Statistical Society. Series A (General) |
| Schlagworte: | Iterative Learning Model Building Inference Bayes Theorem Sampling Theory Predictive Distribution Diagnostic Check Transformations Serial Correlation Bad Values mehr... |
| Zusammenfassung: | Scientific learning is an iterative process employing Criticism and Estimation. Correspondingly the formulated model factors into two complementary parts--a predictive part allowing model criticism, and a Bayes posterior part allowing estimation. Implications for significance tests, the theory of precise measurement and for ridge estimates are considered. Predictive checking functions for transformation, serial correlation, bad values, and their relation with Bayesian options are considered. Robustness is seen from a Bayesian viewpoint and examples are given. For the bad value problem a comparison with M estimators is made. |
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| ISSN: | 00359238 |
| DOI: | 10.2307/2982063 |