numpy.random.beta

numpy.random.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

System Message: WARNING/2 (f(x; a,b) = \frac{1}{B(\alpha, \beta)} x^{\alpha - 1} (1 - x)^{\beta - 1}, )

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where the normalization, B, is the beta function,

System Message: WARNING/2 (B(\alpha, \beta) = \int_0^1 t^{\alpha - 1} (1 - t)^{\beta - 1} dt. )

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It is often seen in Bayesian inference and order statistics.

Note

New code should use the beta method of a default_rng() instance instead; see random-quick-start.

Parameters

afloat or array_like of floats

Alpha, positive (>0).

bfloat or array_like of floats

Beta, positive (>0).

sizeint 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

outndarray or scalar

Drawn samples from the parameterized beta distribution.

See also

Generator.beta

which should be used for new code.

numpy.random.RandomState.zipf numpy.random.binomial