statsmodels.regression.quantile_regression.QuantRegResults.cov_HC1 static QuantRegResults.cov_HC1() See statsmodels.RegressionResults

statsmodels.discrete.discrete_model.CountResults.llr static CountResults.llr()

statsmodels.sandbox.regression.gmm.LinearIVGMM.gradient_momcond LinearIVGMM.gradient_momcond(params, **kwds) [source]

statsmodels.iolib.foreign.StataReader.variables StataReader.variables() [source] Returns a list of the dataset?s StataVariables objects.

statsmodels.stats.sandwich_covariance.se_cov statsmodels.stats.sandwich_covariance.se_cov(cov) get standard deviation from covariance matrix just a shorthand function np.sqrt(np.diag(cov)) Parameters: cov : array_like, square covariance matrix Returns: std : ndarray standard deviation from diagonal of cov

statsmodels.discrete.discrete_model.DiscreteResults.bse static DiscreteResults.bse()

statsmodels.discrete.discrete_model.DiscreteResults.prsquared static DiscreteResults.prsquared() [source]

statsmodels.regression.quantile_regression.QuantRegResults.compare_lm_test QuantRegResults.compare_lm_test(restricted, demean=True, use_lr=False) Use Lagrange Multiplier test to test whether restricted model is correct Parameters: restricted : Result instance The restricted model is assumed to be nested in the current model. The result instance of the restricted model is required to have two attributes, residual sum of squares, ssr, residual degrees of freedom, df_resid. demean : bool Fl

statsmodels.regression.quantile_regression.QuantRegResults class statsmodels.regression.quantile_regression.QuantRegResults(model, params, normalized_cov_params=None, scale=1.0, cov_type='nonrobust', cov_kwds=None, use_t=None) [source] Results instance for the QuantReg model Methods HC0_se() HC1_se() HC2_se() HC3_se() aic() bic() bse() centered_tss() compare_f_test(restricted) use F test to test whether restricted model is correct compare_lm_test(restricted[, demean, use_lr

statsmodels.tsa.vector_ar.var_model.VARProcess.mean VARProcess.mean() [source] Mean of stable process Lutkepohl eq. 2.1.23