A general type of statistical distribution which is related to the gamma distribution. Beta distributions have two free parameters, which are labeled according to one of two notational conventions. The usual definition calls these and , and the other uses and (Beyer 1987, p. 534). The beta distribution is used as a prior distribution for binomial proportions in Bayesian analysis (Evans et al. 2000, p. 34). The above plots are for various values of with and ranging from 0.25 to 3.00.
The domain is , and the probability function and distribution function are given by
(1)
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(2)
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(3)
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where is the beta function, is the regularized beta function, and . The beta distribution is implemented in the Wolfram Language as BetaDistribution[alpha, beta].
The distribution is normalized since
(4)
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The characteristic function is
(5)
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(6)
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where is a confluent hypergeometric function of the first kind.
The raw moments are given by
(7)
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(8)
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(Papoulis 1984, p. 147), and the central moments by
(9)
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where is a hypergeometric function.
The mean, variance, skewness, and kurtosis excess are therefore given by
(10)
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(11)
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(12)
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(13)
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The mode of a variate distributed as is
(14)
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