Poisson model Jacobian of the log-likelihood for each observation
Parameters : | params : array-like
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Returns : | The score vector of the model 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\beta