jax.scipy.stats.cauchy.logsf

jax.scipy.stats.cauchy.logsf(x, loc=0, scale=1)

Cauchy distribution log survival function.

JAX implementation of scipy.stats.cauchy logsf

The survival function is defined as

\[f_{sf}(x) = 1 - f_{cdf}(x)\]

where \(f_{cdf}(x)\) is the cumulative distribution function, jax.scipy.stats.cauchy.cdf().

Parameters:

• x (Array | ndarray | bool | number | bool | int | float | complex) – arraylike, value at which to evaluate the SF

• 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 logsf values.

Return type:

Array

See also

• jax.scipy.stats.cauchy.cdf()

• jax.scipy.stats.cauchy.pdf()

• jax.scipy.stats.cauchy.sf()

• jax.scipy.stats.cauchy.logcdf()

• jax.scipy.stats.cauchy.logpdf()

• jax.scipy.stats.cauchy.isf()

• jax.scipy.stats.cauchy.ppf()