jax.scipy.stats.gennorm.logpdf#

jax.scipy.stats.gennorm.logpdf(x, beta)[source]#

Generalized normal log probability distribution function.

JAX implementation of scipy.stats.gennorm logpdf.

The generalized normal probability distribution function is defined as

\[f(x, \beta) = \frac{\beta}{2\Gamma(1/\beta)}\exp(-|x|^\beta)\]

where \(\Gamma\) is the gamma() function, and \(\beta > 0\).

Parameters:

x (Array | ndarray | bool_ | number | bool | int | float | complex) – arraylike, value at which to evaluate the PDF
beta (Array | ndarray | bool_ | number | bool | int | float | complex) – arraylike, distribution shape parameter

Returns:

array of logpdf values.

Return type:

Array

jax.scipy.stats.gennorm.logpdf