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Low structure imprecise predictive inference for Bayes' problem

This paper presents direct conditional imprecise probabilities for the number of successes in a finite number of future trials, given information about a finite number of past trials. A simple underlying process determining failures or successes is assumed, related to Bayes' postulate, and Hill's A(n) assumption is used. The results are related to the type of predictive inference known as low structure or black-box inference.
Year of publication:
1998
Authors: Coolen, F. P. A.
Published in:
Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 36.1998, 4, p. 349-357
Publisher: Elsevier
Keywords: A(n) Black-box inference Direct conditional probabilities Fundamental problem of practical statistics Fundamental theorem of probability Imprecise probabilities Low stochastic structure Predictive inference
Type of publication: Article
Source:
Persistent link: https://ebvufind01.dmz1.zbw.eu/10005138283
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