statsmodels.discrete.discrete_model.NegativeBinomial.loglike¶

NegativeBinomial.loglike(params)[source]

Loglikelihood for negative binomial model

Parameters: params (array-like) – The parameters of the model. If loglike_method is nb1 or nb2, then the ancillary parameter is expected to be the last element. llf – The loglikelihood value at params float

Notes

Following notation in Greene (2008), with negative binomial heterogeneity parameter $$\alpha$$:

$\begin{split}\lambda_i &= exp(X\beta) \\ \theta &= 1 / \alpha \\ g_i &= \theta \lambda_i^Q \\ w_i &= g_i/(g_i + \lambda_i) \\ r_i &= \theta / (\theta+\lambda_i) \\ ln \mathcal{L}_i &= ln \Gamma(y_i+g_i) - ln \Gamma(1+y_i) + g_iln (r_i) + y_i ln(1-r_i)\end{split}$

where :mathQ=0 for NB2 and geometric and $$Q=1$$ for NB1. For the geometric, $$\alpha=0$$ as well.