numpy.random.beta¶

numpy.random.beta(a, b, size=None)¶

The Beta distribution over [0, 1].

The Beta distribution is a special case of the Dirichlet distribution, and is related to the Gamma distribution. It has the probability distribution function

$f(x; a,b) = \frac{1}{B(\alpha, \beta)} x^{\alpha - 1} (1 - x)^{\beta - 1},$

where the normalisation, B, is the beta function,

$B(\alpha, \beta) = \int_0^1 t^{\alpha - 1} (1 - t)^{\beta - 1} dt.$

It is often seen in Bayesian inference and order statistics.

Parameters :

Parameters :	a : float Alpha, non-negative. b : float Beta, non-negative. size : tuple of ints, optional The number of samples to draw. The output is packed according to the size given.
Returns :	out : ndarray Array of the given shape, containing values drawn from a Beta distribution.

a : float

Alpha, non-negative.

b : float

Beta, non-negative.

size : tuple of ints, optional

The number of samples to draw. The output is packed according to the size given.

Returns :

out : ndarray

Array of the given shape, containing values drawn from a Beta distribution.

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