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・ Probabilistic programming language
・ Probabilistic proposition
・ Probabilistic relevance model
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・ Probabilistic Turing machine
・ Probabilistic voting model
・ Probabilistic-based design optimization
・ Probabilistically checkable proof
・ Probability
・ Probability amplitude
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・ Probability axioms
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Probability box
・ Probability current
・ Probability density function
・ Probability derivations for making rank-based hands in Omaha hold 'em
・ Probability distribution
・ Probability distribution function
・ Probability in the Engineering and Informational Sciences
・ Probability integral transform
・ Probability interpretations
・ Probability mass function
・ Probability matching
・ Probability measure
・ Probability Moon
・ Probability of default
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Probability box : ウィキペディア英語版
Probability box


A probability box (or p-box) is a characterization of an uncertain number consisting of both aleatoric and epistemic uncertainties that is often used in risk analysis or quantitative uncertainty modeling where numerical calculations must be performed. Probability bounds analysis is used to make arithmetic and logical calculations with p-boxes.
An example p-box is shown in the figure at right for an uncertain number ''x'' consisting of a left (upper) bound and a right (lower) bound on the probability distribution for ''x''. The bounds are coincident for values of ''x'' below 0 and above 24. The bounds may have almost any shapes, including step functions, so long as they are monotonically increasing and do not cross each other. A p-box is used to express simultaneously incertitude (epistemic uncertainty), which is represented by the breadth between the left and right edges of the p-box, and variability (aleatory uncertainty), which is represented by the overall slant of the p-box.
==Interpretation==

There are dual interpretations of a p-box. It can be understood as bounds on the cumulative probability associated with any ''x''-value. For instance, in the p-box depicted at right, the probability that the value will be 2.5 or less is between 4% and 36%. A p-box can also be understood as bounds on the ''x''-value at any particular probability level. In the example, the 95th percentile is sure to be between 9 and 16.
If the left and right bounds of a p-box are sure to enclose the unknown distribution, the bounds are said to be ''rigorous'', or absolute. The bounds may also be the tightest possible such bounds on the distribution function given the available information about it, in which case the bounds are therefore said to be ''best-possible''. It may commonly be the case, however, that not every distribution that lies within these bounds is a possible distribution for the uncertain number, even when the bounds are rigorous and best-possible.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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