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NegativeBinomial.resid_dev()

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))

doc_statsmodels
doc_statsmodels
2017-01-18 16:12:45
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