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:
Dec 16, 2024