statsmodels.genmod.families.family.Binomial.resid_dev¶
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Binomial.
resid_dev
(endog, mu, scale=1.0)[source]¶ Binomial deviance residuals
Parameters: endog : array-like
Endogenous response variable
mu : array-like
Fitted mean response variable
scale : float, optional
An optional argument to divide the residuals by scale. The default is 1.
Returns: resid_dev : array
Deviance residuals as defined below
Notes
If the endogenous variable is binary:
\[resid\_dev_i = sign(Y_i - \mu_i) * \sqrt{-2 * \log(I_{1,i} * \mu_i + I_{0,i} * (1 - \mu_i))}\]where \(I_{1,i}\) is an indicator function that evalueates to 1 if \(Y_i = 1\). and \(I_{0,i}\) is an indicator function that evaluates to 1 if \(Y_i = 0\).
If the endogenous variable is binomial:
\[resid\_dev_i = sign(Y_i - \mu_i) \sqrt{2 * n_i * (Y_i * \log(Y_i / \mu_i) + (1 - Y_i) * \log(1 - Y_i)/(1 - \mu_i))}\]where \(Y_i\) and \(n\) are as defined in Binomial.initialize.