jax.scipy.stats.t.logpdf#
- jax.scipy.stats.t.logpdf(x, df, loc=0, scale=1)[source]#
Student’s T log probability distribution function.
JAX implementation of
scipy.stats.t
logpdf
.The Student’s T probability distribution function is given by
\[f(x, \nu) = \frac{\Gamma((\nu + 1)/2)}{\sqrt{\pi\nu}\Gamma(\nu/2)}(1 + x^2/\nu)^{(\nu+1)/2}\]Where \(\Gamma\) is the
gamma()
function, and \(\nu > 0\) is the degrees of freedom (JAX follows the scipy convention of naming thisdf
).- Parameters:
x (Array | ndarray | bool | number | bool | int | float | complex) – arraylike, value at which to evaluate the PDF
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 logpdf values.
- Return type:
See also