pymc.Kumaraswamy#

class pymc.Kumaraswamy(name, *args, rng=None, dims=None, initval=None, observed=None, total_size=None, transform=UNSET, **kwargs)[source]#

Kumaraswamy log-likelihood.

The pdf of this distribution is

\[f(x \mid a, b) = abx^{a-1}(1-x^a)^{b-1}\]

(Source code, png, hires.png, pdf)

../../../_images/pymc-Kumaraswamy-1.png

Support

\(x \in (0, 1)\)

Mean

\(b B(1 + \tfrac{1}{a}, b)\)

Variance

\(b B(1 + \tfrac{2}{a}, b) - (b B(1 + \tfrac{1}{a}, b))^2\)

Parameters
atensor_like of float

a > 0.

btensor_like of float

b > 0.

Methods

Kumaraswamy.__init__(*args, **kwargs)

Kumaraswamy.dist(a, b, *args, **kwargs)

Creates a tensor variable corresponding to the cls distribution.

Kumaraswamy.logcdf(a, b)

Compute the log of cumulative distribution function for the Kumaraswamy distribution at the specified value.

Kumaraswamy.logp(a, b)

Calculate log-probability of Kumaraswamy distribution at specified value.

Kumaraswamy.moment(size, a, b)

Attributes

rv_op