# pymc.Logistic#

class pymc.Logistic(name, *args, rng=None, dims=None, initval=None, observed=None, total_size=None, transform=UNSET, **kwargs)[source]#

Logistic log-likelihood.

The pdf of this distribution is

$f(x \mid \mu, s) = \frac{\exp\left(-\frac{x - \mu}{s}\right)}{s \left(1 + \exp\left(-\frac{x - \mu}{s}\right)\right)^2}$
 Support $$x \in \mathbb{R}$$ Mean $$\mu$$ Variance $$\frac{s^2 \pi^2}{3}$$
Parameters
mutensor_like of float, default 0

Mean.

stensor_like of float, default 1

Scale (s > 0).

Methods

 Logistic.__init__(*args, **kwargs) Logistic.dist([mu, s]) Creates a tensor variable corresponding to the cls distribution. Logistic.logcdf(mu, s) Compute the log of the cumulative distribution function for Logistic distribution at the specified value. Logistic.moment(size, mu, s)

Attributes

 rv_op