Chi

class pymc_extras.distributions.Chi(name, nu, **kwargs)

\(\chi\) log-likelihood.

The pdf of this distribution is

\[f(x \mid \nu) = \frac{x^{\nu - 1}e^{-x^2/2}}{2^{\nu/2 - 1}\Gamma(\nu/2)}\]

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

Support	\(x \in [0, \infty)\)
Mean	\(\sqrt{2}\frac{\Gamma((\nu + 1)/2)}{\Gamma(\nu/2)}\)
Variance	\(\nu - 2\left(\frac{\Gamma((\nu + 1)/2)}{\Gamma(\nu/2)}\right)^2\)

Parameters:

nu (tensor_like of float) – Degrees of freedom (nu > 0).

Examples

__init__()

Methods

__init__()
chi_dist(nu, size)
dist(nu, **kwargs)