pymc.AsymmetricLaplace#

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

Asymmetric-Laplace log-likelihood.

The pdf of this distribution is

\[\begin{split}{f(x|\\b,\kappa,\mu) = \left({\frac{\\b}{\kappa + 1/\kappa}}\right)\,e^{-(x-\mu)\\b\,s\kappa ^{s}}}\end{split}\]

where

\[s = sgn(x-\mu)\]

Support

\(x \in \mathbb{R}\)

Mean

\(\mu-\frac{\\\kappa-1/\kappa}b\)

Variance

\(\frac{1+\kappa^{4}}{b^2\kappa^2 }\)

Parameters
kappatensor_like of float

Symmetry parameter (kappa > 0).

mutensor_like of float

Location parameter.

btensor_like of float

Scale parameter (b > 0).

See Also:
——–
`Reference <https://en.wikipedia.org/wiki/Asymmetric_Laplace_distribution>`_

Methods

AsymmetricLaplace.__init__(*args, **kwargs)

AsymmetricLaplace.dist(kappa, mu, b, *args, ...)

Creates a tensor variable corresponding to the cls distribution.

AsymmetricLaplace.logp(b, kappa, mu)

Calculate log-probability of Asymmetric-Laplace distribution at specified value.

AsymmetricLaplace.moment(size, b, kappa, mu)

Attributes

rv_class

rv_op