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DempsterShafer theory and statistical inference with weak beliefs
, 2008
"... DempsterShafer (DS) theory is a powerful tool for probabilistic reasoning and decisionmaking based on a formal calculus for combining statistical and nonstatistical evidence, as represented by a system of belief functions. DS theory has been widely used in computer science and engineering applica ..."
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Cited by 21 (16 self)
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DempsterShafer (DS) theory is a powerful tool for probabilistic reasoning and decisionmaking based on a formal calculus for combining statistical and nonstatistical evidence, as represented by a system of belief functions. DS theory has been widely used in computer science and engineering
DEMPSTERSHAFER INFERENCE WITH WEAK BELIEFS
"... Beliefs specified for predicting an unobserved realization of pivotal variables in the context of the fiducial and DempsterShafer (DS) inference can be weakened for credible inference. We consider predictive random sets for predicting an unobserved random sample from a known distribution, e.g., t ..."
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Cited by 15 (11 self)
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Beliefs specified for predicting an unobserved realization of pivotal variables in the context of the fiducial and DempsterShafer (DS) inference can be weakened for credible inference. We consider predictive random sets for predicting an unobserved random sample from a known distribution, e
Combination of evidence in DempsterShafer theory
, 2002
"... DempsterShafer theory offers an alternative to traditional probabilistic theory for the mathematical representation of uncertainty. The significant innovation of this framework is that it allows for the allocation of a probability mass to sets or intervals. DempsterShafer theory does not require a ..."
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Cited by 79 (2 self)
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DempsterShafer theory offers an alternative to traditional probabilistic theory for the mathematical representation of uncertainty. The significant innovation of this framework is that it allows for the allocation of a probability mass to sets or intervals. DempsterShafer theory does not require
A defect in DempsterShafer theory
 InProceedings of the Tenth Conference on Uncertainty in Arti cial Intelligence
, 1994
"... By analyzing the relationships among chance, weight of evidence and degree ofbelief, it is shown that the assertion \chances are special cases of belief functions " and the assertion \Dempster's rule can be used to combine belief functions based on distinct bodies of evidence " togeth ..."
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Cited by 28 (20 self)
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; together lead to an inconsistency in DempsterShafer theory. To solve this problem, some fundamental postulates of the theory must be rejected. A new approach for uncertainty management is introduced, which shares many intuitive ideas with DS theory, while avoiding this problem. 1
The DempsterShafer calculus for statisticians
 International Journal of Approximate Reasoning
, 2007
"... The DempsterShafer (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 “ ..."
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Cited by 46 (1 self)
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The DempsterShafer (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
DempsterShafer theory of evidence
, 1994
"... comprehensive comparison between generalized incidence calculus and the ..."
21 Generalizing the Dempster–Shafer Theory to Fuzzy Sets
"... Abstract. With the desire to manage imprecise and vague information in evidential reasoning, several attempts have been made to generalize the Dempster–Shafer (D– S) theory to deal with fuzzy sets. However, the important principle of the D–S theory, that the belief and plausibility functions are tre ..."
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Abstract. With the desire to manage imprecise and vague information in evidential reasoning, several attempts have been made to generalize the Dempster–Shafer (D– S) theory to deal with fuzzy sets. However, the important principle of the D–S theory, that the belief and plausibility functions
Submitted to the Statistical Science DempsterShafer Theory and Statistical Inference with Weak Beliefs
"... Abstract. DempsterShafer (DS) theory is a powerful tool for probabilistic reasoning based on a formal calculus for combining evidence. DS theory has been widely used in computer science and engineering applications, but has yet to reach the statistical mainstream, perhaps because the DS belief func ..."
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Abstract. DempsterShafer (DS) theory is a powerful tool for probabilistic reasoning based on a formal calculus for combining evidence. DS theory has been widely used in computer science and engineering applications, but has yet to reach the statistical mainstream, perhaps because the DS belief
Prioritizing Intrusion Analysis Using DempsterShafer Theory
"... Intrusion analysis and incident management remains a difficult problem in practical network security defense. The root cause of this problem is the large rate of false positives in the sensors used by Intrusion Detection System (IDS) systems, reducing the value of the alerts to an administrator. Sta ..."
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Cited by 4 (3 self)
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. Standard Bayesian theory has not been effective in this regard because of the lack of good prior knowledge. This paper presents an approach to handling such uncertainty without the need for prior information, through the DempsterShafer (DS) theory. We address a number of practical but fundamental issues
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