statsmodels.discrete.discrete_model.CountModel¶
- class statsmodels.discrete.discrete_model.CountModel(endog, exog, offset=None, exposure=None, missing='none', check_rank=True, **kwargs)[source]¶
- Attributes:
endog_names
Names of endogenous variables.
exog_names
Names of exogenous variables.
Methods
cdf
(X)The cumulative distribution function of the model.
cov_params_func_l1
(likelihood_model, xopt, ...)Computes cov_params on a reduced parameter space corresponding to the nonzero parameters resulting from the l1 regularized fit.
fit
([start_params, method, maxiter, ...])Fit the model using maximum likelihood.
fit_regularized
([start_params, method, ...])Fit the model using a regularized maximum likelihood.
from_formula
(formula, data[, subset, drop_cols])Create a Model from a formula and dataframe.
hessian
(params)The Hessian matrix of the model.
information
(params)Fisher information matrix of model.
Initialize is called by statsmodels.model.LikelihoodModel.__init__ and should contain any preprocessing that needs to be done for a model.
loglike
(params)Log-likelihood of model.
pdf
(X)The probability density (mass) function of the model.
predict
(params[, exog, exposure, offset, linear])Predict response variable of a count model given exogenous variables
score
(params)Score vector of model.
Properties
Names of endogenous variables.
Names of exogenous variables.