Expertises : procédures statistiques d'aide à la décision
| dc.creator | Morel, Guy | |
| dc.date | 2006-02-27 | |
| dc.date.accessioned | 2026-07-07T08:07:35Z | |
| dc.date.available | 2026-07-07T08:07:35Z | |
| dc.description | In this study, we introduce a new approach to statistical decision theory. Without using a loss function, we select good decision rules to choice between two hypotheses. We call them "experts". They are globally unbiased but also conditionally unbiased on a family of events. We do not try to define the best expert. We define a probability distribution on the space of "experts". The measure of evidence for a hypothesis is the inductive probability of experts that decide this hypothesis, we call this measure: a "vote". We compare this point of view with the p-values. For some family of hypotheses, the "votes" can define a probability on the space of parameters. We compare these results with the Bayes posterior distributions. We study in detail real-parameter families of distributions with monotone likelihood ratio and multiparameter exponential families. | |
| dc.identifier | https://arxiv.org/abs/math/0602611 | |
| dc.identifier | http://arxiv.org/abs/math/0602611 | |
| dc.identifier | Expertises : procédures statistiques d'aide à la décision (1997) 175 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/130982 | |
| dc.subject | Statistics Theory | |
| dc.subject | 62A, 62C, 62f, 62P | |
| dc.title | Expertises : procédures statistiques d'aide à la décision | |
| dc.type | text |