Imprecise probability
Probability theory for low quality data / From Wikipedia, the free encyclopedia
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Imprecise probability generalizes probability theory to allow for partial probability specifications, and is applicable when information is scarce, vague, or conflicting, in which case a unique probability distribution may be hard to identify. Thereby, the theory aims to represent the available knowledge more accurately. Imprecision is useful for dealing with expert elicitation, because:
- People have a limited ability to determine their own subjective probabilities and might find that they can only provide an interval.
- As an interval is compatible with a range of opinions, the analysis ought to be more convincing to a range of different people.