Measuring the effect of observations on Bayes factors
| Autor: | L. I. Pettit, K. D. S. Young |
|---|---|
| Rok vydání: | 1990 |
| Předmět: |
Statistics and Probability
Polynomial regression Bayes' rule Applied Mathematics General Mathematics Linear model Bayes factor Agricultural and Biological Sciences (miscellaneous) Measure (mathematics) Ordinate Outlier Statistics Log-linear model Statistics Probability and Uncertainty General Agricultural and Biological Sciences Mathematics |
| Zdroj: | Biometrika. 77:455-466 |
| ISSN: | 1464-3510 0006-3444 |
| Popis: | SUMMARY In this paper we consider a measure of the effect of single observations on a logarithmic Bayes factor defined via the difference in the logarithms of the Bayes factors conditional first on all the data and then omitting an observation. The measure is related to the conditional predictive ordinate. The form of the measure and examples of its use are presented for a variety of situations, normal samples, linear models, log linear models and the checking of distributional assumptions. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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