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Nonparametric predictive inference and interval probability.

Augustin, T. and Coolen, F. P. A. (2004) 'Nonparametric predictive inference and interval probability.', Journal of statistical planning and inference., 124 (2). pp. 251-272.

Abstract

The assumption A(n), proposed by Hill (J. Amer. Statist. Assoc. 63 (1968) 677), provides a natural basis for low structure non-parametric predictive inference, and has been justified in the Bayesian framework. This paper embeds A(n)-based inference into the theory of interval probability, by showing that the corresponding bounds are totally monotone F-probability and coherent. Similar attractive internal consistency results are proven to hold for conditioning and updating.

Item Type:Article
Keywords:A(n), Capacities, Conditioning, Consistency, Imprecise probabilities, Interval probability, Non-parametrics, Low structure inference, Predictive inference, Updating.
Full text:Full text not available from this repository.
Publisher Web site:http://dx.doi.org/10.1016/j.jspi.2003.07.003
Record Created:26 Apr 2007
Last Modified:31 Mar 2010 12:08

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