pymc.HurdleLogNormal#
- class pymc.HurdleLogNormal(name, psi, mu=0, sigma=None, tau=None, **kwargs)[source]#
Hurdle LogNormal log-likelihood.
\[\begin{split}f(x \mid \psi, \mu, \sigma) = \left\{ \begin{array}{l} (1 - \psi) \ \text{if } x = 0 \\ \psi \frac{\text{LogNormalPDF}(x \mid \mu, \sigma))} {1 - \text{LogNormalCDF}(\epsilon \mid \mu, \sigma)} \ \text{if } x=1,2,3,\ldots \end{array} \right.\end{split}\]where \(\epsilon\) is the machine precision.
- Parameters:
- psitensor_like of
float Expected proportion of LogNormal draws (0 < psi < 1)
- mutensor_like of
float, default 0 Location parameter.
- sigmatensor_like of
float, optional Standard deviation. (sigma > 0). (only required if tau is not specified). Defaults to 1.
- tautensor_like of
float, optional Scale parameter (tau > 0). (only required if sigma is not specified). Defaults to 1.
- psitensor_like of
Methods
HurdleLogNormal.dist(psi[, mu, sigma, tau])