# statsmodels.genmod.families.family.Binomial.resid_dev¶

Binomial.resid_dev(endog, mu, var_weights=1.0, scale=1.0)

The deviance residuals

Parameters: endog (array-like) – The endogenous response variable mu (array-like) – The inverse of the link function at the linear predicted values. var_weights (array-like) – 1d array of variance (analytic) weights. The default is 1. scale (float, optional) – An optional scale argument. The default is 1. resid_dev – Deviance residuals as defined below. float

Notes

The deviance residuals are defined by the contribution D_i of observation i to the deviance as

$resid\_dev_i = sign(y_i-\mu_i) \sqrt{D_i}$

D_i is calculated from the _resid_dev method in each family. Distribution-specific documentation of the calculation is available there.