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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 Cumulative distribution function ： ウィキペディア英語版 Cumulative distribution function In probability theory and statistics, the cumulative distribution function (CDF), or just distribution function, describes the probability that a real-valued random variable ''X'' with a given probability distribution will be found to have a value less than or equal to ''x''. In the case of a continuous distribution, it gives the area under the probability density function from minus infinity to ''x''. Cumulative distribution functions are also used to specify the distribution of multivariate random variables. ==Definition== The cumulative distribution function of a real-valued random variable ''X'' is the function given by :$F\_X(x)\; =\; \backslash operatorname(X\backslash leq\; x),$ where the right-hand side represents the probability that the random variable ''X'' takes on a value less than or equal to ''x''. The probability that ''X'' lies in the semi-closed interval (''a'', ''b''], where ''a''  <  ''b'', is therefore : In the definition above, the "less than or equal to" sign, "≤", is a convention, not a universally used one (e.g. Hungarian literature uses "<"), but is important for discrete distributions. The proper use of tables of the binomial and Poisson distributions depends upon this convention. Moreover, important formulas like Paul Lévy's inversion formula for the characteristic function also rely on the "less than or equal" formulation. If treating several random variables ''X'', ''Y'', ... etc. the corresponding letters are used as subscripts while, if treating only one, the subscript is usually omitted. It is conventional to use a capital ''F'' for a cumulative distribution function, in contrast to the lower-case ''f'' used for probability density functions and probability mass functions. This applies when discussing general distributions: some specific distributions have their own conventional notation, for example the normal distribution. The CDF of a continuous random variable ''X'' can be expressed as the integral of its probability density function ƒX as follows: :$F\_X(x)\; =\; \backslash int\_^x\; f\_X(t)\backslash ,dt.$ In the case of a random variable ''X'' which has distribution having a discrete component at a value ''b'', :$\backslash operatorname(X=b)\; =\; F\_X(b)\; -\; \backslash lim\_\{x\; \backslash to\; b^\{-\}\}\; F\_X(x).$ If ''FX'' is continuous at ''b'', this equals zero and there is no discrete component at ''b''. 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「Cumulative distribution function」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.