jax.scipy.stats.pareto.logcdf#
- jax.scipy.stats.pareto.logcdf(x, b, loc=0, scale=1)[source]#
Pareto log cumulative distribution function.
JAX implementation of
scipy.stats.paretologcdf.The Pareto cumulative distribution function is given by
\[\begin{split}F(x, b) = \begin{cases} 1 - x^{-b} & x \ge 1\\ 0 & x < 1 \end{cases}\end{split}\]and is defined for \(b > 0\).
- Parameters:
x (Array | ndarray | bool | number | bool | int | float | complex | TypedNdArray) – arraylike, value at which to evaluate the CDF
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 logCDF values.
- Return type: