pymc.ChiSquared

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

\(\chi^2\) 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)

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