scikits.statsmodels.discrete.discrete_model.Poisson

class scikits.statsmodels.discrete.discrete_model.Poisson(endog, exog=None)

Poisson model for count data

Parameters :

endog : array-like

1-d array of the response variable.

exog : array-like

exog is an n x p array where n is the number of observations and p is the number of regressors including the intercept if one is included in the data.

Attributes

endog	array	A reference to the endogenous response variable
exog	array	A reference to the exogenous design.

Methods

cdf(X)	Poisson model cumulative distribution function
fit(**kwargs[, start_params, method, ...])	Fit the model using maximum likelihood.
hessian(params)	Poisson model Hessian matrix of the loglikelihood
information(params)	Fisher information matrix of model
initialize()	Initialize is called by
loglike(params)	Loglikelihood of Poisson model
pdf(X)	Poisson model probability mass function
predict([exog, linear])	Predict response variable of a model given exogenous variables.
score(params)	Poisson model score (gradient) vector of the log-likelihood