statsmodels.discrete.discrete_model.Poisson.score¶
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Poisson.
score
(params)[source]¶ 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
\[\ln\lambda_{i}=x_{i}\beta\]