pymc.ChiSquared#

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

\(\chi^2\) log-likelihood.

The pdf of this distribution is

\[f(x \mid \nu) = \frac{x^{(\nu-2)/2}e^{-x/2}}{2^{\nu/2}\Gamma(\nu/2)}\]

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

../../../_images/pymc-ChiSquared-1.png

Support

\(x \in [0, \infty)\)

Mean

\(\nu\)

Variance

\(2 \nu\)
Parameters
nutensor_like of float

Degrees of freedom (nu > 0).

Methods

ChiSquared.__init__(*args, **kwargs)

ChiSquared.dist(nu, *args, **kwargs)

Creates a tensor variable corresponding to the cls distribution.

ChiSquared.logcdf(nu)

ChiSquared.logp(nu)

ChiSquared.moment(size, nu)

Attributes

rv_op