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翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Imprecise probability ： ウィキペディア英語版 Imprecise probability 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. == Introduction == Uncertainty is traditionally modelled by a probability distribution, as argued by Kolmogorov, Laplace, de Finetti, Ramsey, Cox, Lindley, and many others. However, this has not been unanimously accepted by scientists, statisticians, and probabilists: it has been argued that some modification or broadening of probability theory is required, because one may not always be able to provide a probability for every event, particularly when only little information or data is available—an early example of such criticism is Boole's critique of Laplace's work—, or when we wish to model probabilities that a group agrees with, rather than those of a single individual. Perhaps the most straightforward generalization is to replace a single probability specification with an interval specification. Lower and upper probabilities, denoted by $\backslash underline(A)$ and $\backslash overline(A)$, or more generally, lower and upper expectations (previsions), aim to fill this gap: *the special case with $\backslash underline(A)=\backslash overline(A)$ for all events $A$ provides precise probability, whilst *$\backslash underline(A)=0$ and $\backslash overline(A)=1$ represents no constraint at all on the specification of $P(A)$, with a flexible continuum in between. Some approaches, summarized under the name ''nonadditive probabilities'', directly use one of these set functions, assuming the other one to be naturally defined such that $\backslash underline(A^c)=\; 1-\backslash overline(A)$, with $A^c$ the complement of $A$. Other related concepts understand the corresponding intervals $(\backslash overline(A))$ for all events as the basic entity. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Imprecise probability」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.