statsmodels.discrete.discrete_model.CountModel
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class statsmodels.discrete.discrete_model.CountModel(endog, exog, offset=None, exposure=None, missing='none', **kwargs)
[source]
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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 () | 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. |
Attributes
endog_names | Names of endogenous variables |
exog_names | Names of exogenous variables |