Beta Distribution
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)
| |||
|
(2)
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|
(3)
|
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)
|
The characteristic function is
|
(5)
| |||
|
(6)
|
where
is a confluent
hypergeometric function of the first kind.
The raw moments are given by
|
(7)
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|
(8)
|
(Papoulis 1984, p. 147), and the central moments by
|
(9)
|
where
is a hypergeometric
function.
The mean, variance, skewness, and kurtosis are therefore given by
|
(10)
| |||
|
(11)
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![]() |
(12)
| ||
|
(13)
|
The mode of a variate distributed as
is
|
(14)
|

beta distribution

