The Boxer, the Wrestler, and the Coin Flip: A Paradox of Robust Bayesian Inference and Belief Functions
Bayesian inference requires all unknowns to be represented by probability distributions, which awkwardly implies that the probability of an event for which we are completely ignorant (e.g., that the world's greatest boxer would defeat the world's greatest wrestler) must be assigned a parti...
| Veröffentlicht in: | The American Statistician. - American Statistical Association, 1947. - 60(2006), 2, Seite 146-150 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2006
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| Zugriff auf das übergeordnete Werk: | The American Statistician |
| Schlagworte: | Dempster-Shafer theory Epistemic and aleatory uncertainty Foundations of probability Ignorance Robust Bayes Subjective prior distribution Mathematics Information science Behavioral sciences Philosophy |
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