Poisson model score (gradient) vector of the log-likelihood
Parameters: | params : array-like
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Returns: | score : ndarray, 1-D
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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