statsmodels.discrete.discrete_model.Poisson.score_obs¶
-
Poisson.score_obs(params)[source]¶ Poisson model Jacobian of the log-likelihood for each observation
- Parameters
- paramsarray_like
The parameters of the model
- Returns
- scorearray_like
The score vector (nobs, k_vars) of the model evaluated at params
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
\[\ln\lambda_{i}=x_{i}\beta\]