statsmodels.discrete.discrete_model.DiscreteResults.tvalues static DiscreteResults.tvalues() Return the t-statistic for a given parameter estimate.

statsmodels.graphics.mosaicplot.mosaic statsmodels.graphics.mosaicplot.mosaic(data, index=None, ax=None, horizontal=True, gap=0.005, properties= at 0x2ac652f5b6e0>, labelizer=None, title='', statistic=False, axes_label=True, label_rotation=0.0) [source] Create a mosaic plot from a contingency table. It allows to visualize multivariate categorical data in a rigorous and informative way. Parameters: data : dict, pandas.Series, np.ndarray, pandas.DataFrame The contingency table that contai

statsmodels.duration.hazard_regression.PHReg.initialize PHReg.initialize() Initialize (possibly re-initialize) a Model instance. For instance, the design matrix of a linear model may change and some things must be recomputed.

statsmodels.discrete.discrete_model.NegativeBinomial.information NegativeBinomial.information(params) Fisher information matrix of model Returns -Hessian of loglike evaluated at params.

statsmodels.discrete.discrete_model.LogitResults.llf static LogitResults.llf()

statsmodels.genmod.cov_struct.Autoregressive.initialize Autoregressive.initialize(model) Called by GEE, used by implementations that need additional setup prior to running fit. Parameters: model : GEE class A reference to the parent GEE class instance.

statsmodels.discrete.discrete_model.DiscreteModel.initialize DiscreteModel.initialize() [source] Initialize is called by statsmodels.model.LikelihoodModel.__init__ and should contain any preprocessing that needs to be done for a model.

statsmodels.miscmodels.count.PoissonZiGMLE.loglikeobs PoissonZiGMLE.loglikeobs(params)

statsmodels.tsa.arima_model.ARMAResults.mafreq static ARMAResults.mafreq() [source] Returns the frequency of the MA roots. This is the solution, x, to z = abs(z)*exp(2j*np.pi*x) where z are the roots.

statsmodels.discrete.discrete_model.BinaryModel.information BinaryModel.information(params) Fisher information matrix of model Returns -Hessian of loglike evaluated at params.