jax.scipy.stats.chi2.logcdf

jax.scipy.stats.chi2.logcdf(x, df, loc=0, scale=1)

Chi-square log cumulative distribution function.

JAX implementation of scipy.stats.chi2 logcdf.

The cdf is defined as

\[f_{cdf}(x, k) = \int_{-\infty}^x f_{pdf}(y, k)\mathrm{d}y\]

where \(f_{pdf}\) is the probability density function, jax.scipy.stats.chi2.pdf(). JAX follows the scipy convention of using df to denote degrees of freedom.

Parameters:

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

• df (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 logcdf values

Return type:

Array

See also

• jax.scipy.stats.chi2.cdf()

• jax.scipy.stats.chi2.pdf()

• jax.scipy.stats.chi2.sf()

• jax.scipy.stats.chi2.logpdf()

• jax.scipy.stats.chi2.logsf()