This paper relaxes the conventional subjective probability setup by allowing the $\sigma$-algebra on which probabilities are defined to be subjective along with the probability measure. First, the role of the probability domain in existing statistical decision theory is examined. Then the existing theory is extended by characterizing the individual's selection of a probability domain as the outcome of a decision process.
Publié le : 1981-01-14
Classification:
Subjective probability systems,
Bayes rule,
measurable utility,
elicitation of subjective probabilities,
statistical decision theory,
62A15,
62C10
@article{1176345332,
author = {Manski, Charles F.},
title = {Learning and Decision Making when Subjective Probabilities have Subjective Domains},
journal = {Ann. Statist.},
volume = {9},
number = {1},
year = {1981},
pages = { 59-65},
language = {en},
url = {http://dml.mathdoc.fr/item/1176345332}
}
Manski, Charles F. Learning and Decision Making when Subjective Probabilities have Subjective Domains. Ann. Statist., Tome 9 (1981) no. 1, pp. 59-65. http://gdmltest.u-ga.fr/item/1176345332/