7.6.3.15. 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]¶ -
Methods
__init__(endog, exog[, offset, exposure, ...])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])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_namesexog_names