Classic Works of the Dempster-Shafer Theory of Belief Functions - Yager, Ronald R.; Liu, Liping; SpringerLink (Online service) (Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2008)
Classic Works of the Dempster-Shafer Theory of Belief Functions: An Introduction -- New Methods for Reasoning Towards Posterior Distributions Based on Sample Data -- Upper and Lower Probabilities Induced by a Multivalued Mapping -- A Generalization of Bayesian Inference -- On Random Sets and Belief Functions -- Non-Additive Probabilities in the Work of Bernoulli and Lambert -- Allocations of Probability -- Computational Methods for A Mathematical Theory of Evidence -- Constructive Probability -- Belief Functions and Parametric Models -- Entropy and Specificity in a Mathematical Theory of Evidence -- A Method for Managing Evidential Reasoning in a Hierarchical Hypothesis Space -- Languages and Designs for Probability Judgment -- A Set-Theoretic View of Belief Functions -- Weights of Evidence and Internal Conflict for Support Functions -- A Framework for Evidential-Reasoning Systems -- Epistemic Logics, Probability, and the Calculus of Evidence -- Implementing Dempster's Rule for Hierarchical Evidence -- Some Characterizations of Lower Probabilities and Other Monotone Capacities through the use of Möbius Inversion -- Axioms for Probability and Belief-Function Propagation -- Generalizing the Dempster-Shafer Theory to Fuzzy Sets -- Bayesian Updating and Belief Functions -- Belief-Function Formulas for Audit Risk -- Decision Making Under Dempster-Shafer Uncertainties -- Belief Functions: The Disjunctive Rule of Combination and the Generalized Bayesian Theorem -- Representation of Evidence by Hints -- Combining the Results of Several Neural Network Classifiers -- The Transferable Belief Model -- A k-Nearest Neighbor Classification Rule Based on Dempster-Shafer Theory -- Logicist Statistics II: Inference.
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