Updating with incomplete observations

10 years 7 months ago
Updating with incomplete observations
Currently, there is renewed interest in the problem, raised by Shafer in 1985, of updating probabilities when observations are incomplete (or setvalued). This is a fundamental problem, and of particular interest for Bayesian networks. Recently, Gr¨unwald and Halpern have shown that commonly used updating strategies fail here, except under very special assumptions. We propose a new rule for updating probabilities with incomplete observations. Our approach is deliberately conservative: we make no or weak assumptions about the so-called incompleteness mechanism that produces incomplete observations. We model our ignorance about this mechanism by a vacuous lower prevision, a tool from the theory of imprecise probabilities, and we derive a new updating rule using coherence arguments. In general, our rule produces lower posterior probabilities, as well as partially determinate decisions. This is a logical consequence of the ignorance about the incompleteness mechanism. We show how the new ...
Gert de Cooman, Marco Zaffalon
Added 01 Nov 2010
Updated 01 Nov 2010
Type Conference
Year 2003
Where UAI
Authors Gert de Cooman, Marco Zaffalon
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