Dempster, A. P. The Dempster-Shafer calculus for statisticians. (English) Zbl 1274.62053 Int. J. Approx. Reasoning 48, No. 2, 365-377 (2008). Summary: The Dempster-Shafer (DS) theory of probabilistic reasoning is presented in terms of a semantics whereby every meaningful formal assertion is associated with a triple \((p, q, r)\) where \(p\) is the probability “for” the assertion, \(q\) is the probability “against” the assertion, and \(r\) is the probability of “don’t know”. Arguments are presented for the necessity of “don’t know”. Elements of the calculus are sketched, including the extension of a DS model from a margin to a full state space, and DS combination of independent DS uncertainty assessments on the full space. The methodology is applied to inference and prediction from Poisson counts, including an introduction to the use of join-tree model structure to simplify and shorten computation. The relation of DS theory to statistical significance testing is elaborated, introducing along the way the new concept of “dull” null hypothesis. Cited in 54 Documents MSC: 62A01 Foundations and philosophical topics in statistics 60A05 Axioms; other general questions in probability 68T37 Reasoning under uncertainty in the context of artificial intelligence Keywords:Dempster-Shafer calculus; belief functions; state space; Poisson model; join-tree computation; statistical significance; dull null hypothesis PDF BibTeX XML Cite \textit{A. P. Dempster}, Int. J. Approx. Reasoning 48, No. 2, 365--377 (2008; Zbl 1274.62053) Full Text: DOI References: [1] Shafer, G., A mathematical theory of evidence, (1976), Princeton University Press Princeton, New Jeresy · Zbl 0359.62002 [2] Dempster, A.P., New methods for reasoning towards posterior distributions based on sample data, Ann. math. statist., 37, 355-374, (1966) · Zbl 0178.54302 [3] Dempster, A.P., Upper and lower probabilities induced by a multivalued mapping, Ann. math. statist., 38, 325-339, (1967) · Zbl 0168.17501 [4] Dempster, A.P., A generalization of Bayesian inference, J. R. statist. soc. B, 30, 205-247, (1968) · Zbl 0169.21301 [5] Maier, D., The theory of relational data bases, (1983), Computer Science Press Rockville, Maryland [6] Shenoy, P.P.; Shafer, G., Propagating belief functions with local computations, IEEE expert, 1, 43-52, (1986) [7] A. Kong, Multivariate Belief Functions and Graphical Models, Unpublished Ph.D. Thesis. Department of Statistics, Harvard University (1986). [8] Smets, P.; Kennes, R., The transferable belief model, Artif. intell., 66, 191-234, (1994) · Zbl 0807.68087 [9] Feller, W., Probability theory and its applications, (1950), Wiley New York · Zbl 0039.13201 [10] R.G. Almond, Fusion and Propagation of Graphical Belief Models: and Implementation and an Example, Unpublished Ph.D. Thesis. Department of Statistics, Harvard University (1989). [11] Almond, R.G., Graphical belief modeling, (1995), Chapman and Hall London [12] Fisher, R.A., Statistical methods and scientific inference, (1956), Oliver and Boyd Edinburgh · Zbl 0070.36903 [13] L.J. Savage et al., The Foundations of Statistical Inference: a Discussion, Methuen, London, 1962. This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.