statsmodels.genmod.families.links.probit.deriv2 probit.deriv2(p) Second derivative of the link function g??(p) implemented through numerical differentiation

statsmodels.genmod.generalized_estimating_equations.GEEResults.normalized_cov_params GEEResults.normalized_cov_params()

statsmodels.duration.hazard_regression.PHReg class statsmodels.duration.hazard_regression.PHReg(endog, exog, status=None, entry=None, strata=None, offset=None, ties='breslow', missing='drop', **kwargs) [source] Fit the Cox proportional hazards regression model for right censored data. Parameters: endog : array-like The observed times (event or censoring) exog : 2D array-like The covariates or exogeneous variables status : array-like The censoring status values; status=1 indicates that

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

statsmodels.tsa.arima_model.ARMAResults.fittedvalues static ARMAResults.fittedvalues() [source]

statsmodels.genmod.families.links.Link.deriv2 Link.deriv2(p) [source] Second derivative of the link function g??(p) implemented through numerical differentiation

statsmodels.genmod.cov_struct.Exchangeable.update Exchangeable.update(params) [source] Updates the association parameter values based on the current regression coefficients. Parameters: params : array-like Working values for the regression parameters.

statsmodels.sandbox.stats.multicomp.StepDown.get_crit StepDown.get_crit(alpha) [source]

statsmodels.genmod.cov_struct.Independence.initialize Independence.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.sandbox.regression.gmm.NonlinearIVGMM.score_cu NonlinearIVGMM.score_cu(params, epsilon=None, centered=True)