statsmodels.discrete.discrete_model.LogitResults.resid_pearson

LogitResults.resid_pearson

Pearson residuals

Notes

Pearson residuals are defined to be

\[r_j = \frac{(y - M_jp_j)}{\sqrt{M_jp_j(1-p_j)}}\]

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.


Last update: Jun 14, 2024