statsmodels.regression.mixed_linear_model.MixedLMResults.bse static MixedLMResults.bse()

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

statsmodels.discrete.discrete_model.LogitResults.resid_response static LogitResults.resid_response() The response residuals Notes Response residuals are defined to be where .

statsmodels.discrete.discrete_model.LogitResults.resid_pearson static LogitResults.resid_pearson() Pearson residuals Notes Pearson residuals are defined to be where and is the total number of observations sharing the covariate pattern . For now is always set to 1.

statsmodels.discrete.discrete_model.LogitResults.resid_generalized static LogitResults.resid_generalized() [source] Generalized residuals Notes The generalized residuals for the Logit model are defined where . This is the same as the resid_response for the Logit model.

statsmodels.discrete.discrete_model.LogitResults.resid_dev static LogitResults.resid_dev() Deviance residuals Notes Deviance residuals are defined where and is the total number of observations sharing the covariate pattern . For now is always set to 1.

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

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

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

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