statsmodels.genmod.generalized_estimating_equations.GEEResults.llf static GEEResults.llf()

statsmodels.discrete.discrete_model.BinaryModel.cdf BinaryModel.cdf(X) The cumulative distribution function of the model.

statsmodels.genmod.generalized_estimating_equations.GEEResults.initialize GEEResults.initialize(model, params, **kwd)

statsmodels.tsa.arima_model.ARMAResults.normalized_cov_params ARMAResults.normalized_cov_params()

Graphics Goodness of Fit Plots gofplots.qqplot(data[, dist, distargs, a, ...]) Q-Q plot of the quantiles of x versus the quantiles/ppf of a distribution. gofplots.qqline(ax, line[, x, y, dist, fmt]) Plot a reference line for a qqplot. gofplots.qqplot_2samples(data1, data2[, ...]) Q-Q Plot of two samples? quantiles. gofplots.ProbPlot(data[, dist, fit, ...]) Class for convenient construction of Q-Q, P-P, and probability plots. Boxplots boxplots.violinplot(data[, ax, labels, ...]) Make a v

statsmodels.regression.linear_model.OLSResults.f_pvalue static OLSResults.f_pvalue()

statsmodels.regression.linear_model.RegressionResults.bse static RegressionResults.bse() [source]

statsmodels.discrete.discrete_model.ProbitResults.llnull static ProbitResults.llnull()

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

statsmodels.sandbox.regression.try_catdata.labelmeanfilter_str statsmodels.sandbox.regression.try_catdata.labelmeanfilter_str(ys, x) [source]