numpy.random.RandomState.beta

RandomState.beta(a, b, size=None)

Draw samples from a Beta distribution.

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:	`a : float or array_like of floats` Alpha, non-negative. `b : float or array_like of floats` Beta, non-negative. `size : int or tuple of ints, optional` Output shape. If the given shape is, e.g., `(m, n, k)`, then `m * n * k` samples are drawn. If size is `None` (default), a single value is returned if `a` and `b` are both scalars. Otherwise, `np.broadcast(a, b).size` samples are drawn.
Returns:	`out : ndarray or scalar` Drawn samples from the parameterized beta distribution.

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https://docs.scipy.org/doc/numpy-1.15.4/reference/generated/numpy.random.RandomState.beta.html