jax.scipy.stats.pareto.sf

jax.scipy.stats.pareto.sf#

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

Pareto survival function.

JAX implementation of scipy.stats.pareto sf.

The Pareto survival function is given by

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

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

Parameters:

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

Returns:

array of survival function values.

Return type:

Array