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.
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.
|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|
|Date accepted:||No date available|
|Date deposited:||No date available|
|Date of first online publication:||01 January 1970|
|Date first made open access:||No date available|
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