# statsmodels.discrete.discrete_model.Poisson.score¶

method

Poisson.score(params)[source]

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

Parameters
paramsarray-like

The parameters of the model

Returns
scorendarray, 1-D

The score vector of the model, i.e. the first derivative of the loglikelihood function, evaluated at params

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

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