jax.scipy.stats.pareto.logsf#
- jax.scipy.stats.pareto.logsf(x, b, loc=0, scale=1)[source]#
Pareto log survival function.
JAX implementation of
scipy.stats.paretologsf.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 log survival function values.
- Return type: