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On nonparametric predictive inference and abjective Bayesianism

Coolen, F.P.A.



This paper consists of three main parts. First, we give an introduction to Hill’s assumption A (n) and to theory of interval probability, and an overview of recently developed theory and methods for nonparametric predictive inference (NPI), which is based on A (n) and uses interval probability to quantify uncertainty. Thereafter, we illustrate NPI by introducing a variation to the assumption A (n), suitable for inference based on circular data, with applications to several data sets from the literature. This includes attention to comparison of two groups of circular data, and to grouped data. We briefly discuss such inference for multiple future observations. We end the paper with a discussion of NPI and objective Bayesianism.


Coolen, F. (2006). On nonparametric predictive inference and abjective Bayesianism. Journal of Logic, Language and Information, 15(1-2), 21-47.

Journal Article Type Article
Publication Date Jul 1, 2006
Deposit Date Jan 9, 2009
Journal Journal of Logic, Language and Information
Print ISSN 0925-8531
Electronic ISSN 1572-9583
Publisher Springer
Peer Reviewed Peer Reviewed
Volume 15
Issue 1-2
Pages 21-47
Keywords Circular data, Exchangeability, Grouped data, Imprecise probabilities, Interval probability, Objective Bayesianism.
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