Arbeitspapier
Non-Bayesian testing of a stochastic prediction
We propose a method to test a prediction of the distribution of a stochastic process. In a non-Bayesian non-parametric setting, a predicted distribution is tested using a realization of the stochastic process. A test associates a set of realizations for each predicted distribution, on which the prediction passes. So that there are no type I errors, a prediction assigns probability 1 to its test set. Nevertheless, these sets are .small., in the sense that .most.distributions assign it probability 0, and hence there are .few. type II errors. It is also shown that there exists such a test that cannot be manipulated, in the sense that an uninformed predictor who is pretending to know the true distribution is guaranteed to fail on an uncountable number of realizations, no matter what randomized prediction he employs. The notion of a small set we use is category I, described in more detail in the paper.
- Language
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Englisch
- Bibliographic citation
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Series: Discussion Paper ; No. 1418
- Classification
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Wirtschaft
- Subject
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Stochastischer Prozess
Statistischer Test
Wahrscheinlichkeitsrechnung
Theorie
- Event
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Geistige Schöpfung
- (who)
-
Dekel, Eddie
Feinberg, Yossi
- Event
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Veröffentlichung
- (who)
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Northwestern University, Kellogg School of Management, Center for Mathematical Studies in Economics and Management Science
- (where)
-
Evanston, IL
- (when)
-
2005
- Handle
- Last update
-
10.03.2025, 11:45 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Dekel, Eddie
- Feinberg, Yossi
- Northwestern University, Kellogg School of Management, Center for Mathematical Studies in Economics and Management Science
Time of origin
- 2005
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