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'''Upper and lower probabilities''' are representations of [[imprecise probability]]. Whereas [[probability theory]] uses a single number, the [[probability]], to describe how likely an event is to occur, this method uses two numbers: the upper probability of the event and the lower probability of the event.
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Because [[frequentist statistics]] disallows [[metaprobability|metaprobabilities]],{{cn|date=May 2012}} frequentists have had to propose new solutions. [[Cedric Smith (statistician)|Cedric Smith]] and [[Arthur P. Dempster|Arthur Dempster]] each developed a theory of upper and lower probabilities. [[Glenn Shafer]] developed Dempster's theory further, and it is now known as [[Dempster–Shafer theory]]: see also Choquet(1953).
More precisely, in the work of these authors one considers in a [[power set]], <math>P(S)\,\!</math>,  a ''mass'' function <math>m : P(S)\rightarrow R</math> satisfying the conditions
 
:<math>m(\varnothing) = 0 \,\,\,\,\,\,\! ; \,\,\,\,\,\, \sum_{A \in P(X)} m(A) = 1. \,\!</math>
 
In turn, a mass is associated with two non-additive continuous measures called '''belief'''  and '''plausibility''' defined as follows:
 
:<math>\operatorname{bel}(A) = \sum_{B \mid B \subseteq A} m(B)\,\,\,\,;\,\,\,\,
\operatorname{pl}(A) = \sum_{B \mid B \cap A \ne \varnothing} m(B)</math>
 
In the case where <math>S</math> is infinite there can be <math>\operatorname{bel}</math> such that there is no associated mass function. See p. 36 of Halpern (2003). Probability measures are a special case of belief functions in which the mass function assigns positive mass to singletons of the event space only.
 
A different notion of upper and lower probabilities is obtained by the ''lower and upper envelopes'' obtained from a class ''C'' of probability distributions by setting
:<math>\operatorname{env_1}(A) = \inf_{p \in C} p(A)\,\,\,\,;\,\,\,\,
\operatorname{env_2}(A) = \sup_{p \in C} p(A)</math>
 
The upper and lower probabilities are also related with [[probabilistic logic]]: see Gerla (1994).
 
Observe also that a [[necessity measure]] can be seen as a lower probability and a [[possibility measure]] can be seen as an upper probability.
 
==See also==
*[[Possibility theory]]
*[[Fuzzy measure theory]]
*[[Interval finite element]]
 
==References==
*G. Gerla, Inferences in Probability Logic, ''Artificial Intelligence'' 70(1–2):33–52, 1994.  
*J.Y. Halpern 2003 ''Reasoning about Uncertainty'' MIT Press
*J. Y. Halpern and R. Fagin, Two views of belief: Belief as generalized probability and belief as evidence. ''Artificial Intelligence'', 54:275–317, 1992.  
*P. J. Huber, ''Robust Statistics''. Wiley, New York, 1980.
*Saffiotti, A., A Belief-Function Logic, in ''Procs of the 10h AAAI Conference'', San Jose, CA 642–647, 1992.
*Choquet, G., Theory of Capacities, ''Annales de l'Institut Fourier'' 5, 131–295, 1953.
*Shafer, G., ''A Mathematical Theory of Evidence'', (Princeton University Press, Princeton), 1976.
*P. Walley and T. L. Fine, Towards a frequentist theory of upper and lower probability. ''Annals of Statistics'', 10(3):741–761, 1982.
 
[[Category:Exotic probabilities]]
[[Category:Probability bounds analysis]]

Latest revision as of 12:04, 6 November 2014

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