7.2.3.3.6.6. statsmodels.genmod.families.family.NegativeBinomial.resid_dev¶

NegativeBinomial.resid_dev(endog, mu, scale=1.0)[source]¶

Negative Binomial Deviance Residual

Parameters:	endog : array-like endog is the response variable mu : array-like mu is the fitted value of the model scale : float, optional An optional argument to divide the residuals by scale
Returns:	resid_dev : array The array of deviance residuals

Notes

resid_dev = sign(endog-mu) * sqrt(piecewise)

where piecewise is defined as

If $Y_i = 0$:

$$piecewise_i = 2*log(1+alpha*mu)/alpha$$

If $Y_i > 0$:

$$piecewise_i = 2*Y*log(Y/\mu) - 2/\alpha * (1 + \alpha * Y) * \log((1 + \alpha * Y)/(1 + \alpha * \mu))$$