jax.scipy.stats.pareto.logpdf

jax.scipy.stats.pareto.logpdf#

jax.scipy.stats.pareto.logpdf(x, b, loc=0, scale=1)[source]#

Pareto log probability distribution function.

JAX implementation of scipy.stats.pareto logpdf.

The Pareto probability density function is given by

\[\begin{split}f(x, b) = \begin{cases} bx^{-(b+1)} & x \ge 1\\ 0 & x < 1 \end{cases}\end{split}\]

and is defined for \(b > 0\).

Parameters:

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

Returns:

array of logpdf values.

Return type:

Array