# statsmodels.discrete.discrete_model.Poisson.score_obs¶

Poisson.score_obs(params)[source]

Poisson model Jacobian of the log-likelihood for each observation

Parameters: params (array-like) – The parameters of the model score – The score vector (nobs, k_vars) of the model evaluated at params array-like

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

$\ln\lambda_{i}=x_{i}\beta$