statsmodels.discrete.discrete_model.MNLogit.fit MNLogit.fit(start_params=None, method='newton', maxiter=35, full_output=1, disp=1, callback=None, **kwargs) Fit the model using maximum likelihood. The rest of the docstring is from statsmodels.base.model.LikelihoodModel.fit Fit method for likelihood based models Parameters: start_params : array-like, optional Initial guess of the solution for the loglikelihood maximization. The default is an array of zeros. method : str, optional The metho

statsmodels.tsa.vector_ar.var_model.VARResults.long_run_effects VARResults.long_run_effects() Compute long-run effect of unit impulse

statsmodels.discrete.discrete_model.Poisson.fit_regularized Poisson.fit_regularized(start_params=None, method='l1', maxiter='defined_by_method', full_output=1, disp=1, callback=None, alpha=0, trim_mode='auto', auto_trim_tol=0.01, size_trim_tol=0.0001, qc_tol=0.03, **kwargs) [source] Fit the model using a regularized maximum likelihood. The regularization method AND the solver used is determined by the argument method. Parameters: start_params : array-like, optional Initial guess of the sol

statsmodels.tsa.vector_ar.irf.IRAnalysis.lr_effect_cov IRAnalysis.lr_effect_cov(orth=False) [source]

statsmodels.regression.linear_model.GLSAR.initialize GLSAR.initialize()

statsmodels.tsa.arima_model.ARIMA.loglike_kalman ARIMA.loglike_kalman(params, set_sigma2=True) Compute exact loglikelihood for ARMA(p,q) model by the Kalman Filter.

statsmodels.sandbox.regression.gmm.GMMResults.initialize GMMResults.initialize(model, params, **kwd)

statsmodels.tsa.vector_ar.var_model.VAR.score VAR.score(params) Score vector of model. The gradient of logL with respect to each parameter.

statsmodels.sandbox.regression.try_catdata.cat2dummy statsmodels.sandbox.regression.try_catdata.cat2dummy(y, nonseq=0) [source]

statsmodels.nonparametric.kde.KDEUnivariate.entropy static KDEUnivariate.entropy() [source] Returns the differential entropy evaluated at the support Notes Will not work if fit has not been called. 1e-12 is added to each probability to ensure that log(0) is not called.