statsmodels.discrete.discrete_model.LogitResults.resid_dev

LogitResults.resid_dev

Deviance residuals

Notes

Deviance residuals are defined

\[d_j = \pm\left(2\left[Y_j\ln\left(\frac{Y_j}{M_jp_j}\right) + (M_j - Y_j\ln\left(\frac{M_j-Y_j}{M_j(1-p_j)} \right) \right] \right)^{1/2}\]

where

\(p_j = cdf(X\beta)\) and \(M_j\) is the total number of observations sharing the covariate pattern \(j\).

For now \(M_j\) is always set to 1.