On nonparametric predictive inference and abjective Bayesianism

Coolen, F.P.A.

doi:10.1007/s10849-005-9005-7

On nonparametric predictive inference and abjective Bayesianism

Coolen, F.P.A.

Authors

Professor Frank Coolen frank.coolen@durham.ac.uk
Professor

Abstract

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.

Citation

Coolen, F. (2006). On nonparametric predictive inference and abjective Bayesianism. Journal of Logic, Language and Information, 15(1-2), 21-47. https://doi.org/10.1007/s10849-005-9005-7

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
DOI	https://doi.org/10.1007/s10849-005-9005-7
Keywords	Circular data, Exchangeability, Grouped data, Imprecise probabilities, Interval probability, Objective Bayesianism.