Poisson model Jacobian of the log-likelihood for each observation
Parameters: | params : array-like
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Returns: | score : ndarray (nobs, k_vars)
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Notes
\frac{\partial\ln L_{i}}{\partial\beta}=\left(y_{i}-\lambda_{i}\right)x_{i}
for observations i=1,...,n
where the loglinear model is assumed
\ln\lambda_{i}=x_{i}\beta