# revrand.likelihoods.Poisson¶

class revrand.likelihoods.Poisson(tranfcn='exp')

A Poisson likelihood, useful for various Poisson process tasks.

An exponential transformation function and a softplus transformation function have been implemented.

$p(y_i | f_i) = \frac{g(f_i)^{y_i} e^{-g(f_i)}}{y_i!}$

where $$y_i$$ is a target, $$f_i$$ the value of the latent function corresponding to the target, and $$g(\cdot)$$ is the tranformation function, which can be either an exponential function, or a softplus function ($$\log(1 + \exp(f_i)$$).

Parameters: tranfcn (string, optional) – this may be ‘exp’ for an exponential transformation function, or ‘softplus’ for a softplut transformation function.
__init__(tranfcn='exp')

See class docstring.

Methods

 Ey(f) Expected value of the Poisson likelihood. __init__([tranfcn]) See class docstring. cdf(y, f) Cumulative density function of the likelihood. df(y, f) Derivative of Poisson log likelihood w.r.t. f. dp(y, f, *args) Derivative of Bernoulli log likelihood w.r.t.the parameters, $$\theta$$. loglike(y, f) Poisson log likelihood.

Attributes

 params Get this object’s Parameter types.