statsmodels.discrete.discrete_model.Poisson.score

Poisson.score(params)

Poisson model score (gradient) vector of the log-likelihood

Parameters:params (array-like) – The parameters of the model Returns:score – The score vector of the model, i.e. the first derivative of the loglikelihood function, evaluated at params Return type:ndarray, 1-D

Notes

$$\frac{\partial\ln L}{\partial\beta}=\sum_{i=1}^{n}\left(y_{i}-\lambda_{i}\right)x_{i}$$

where the loglinear model is assumed

$$\ln\lambda_{i}=x_{i}\beta$$