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

\[\ln\lambda_{i}=x_{i}\beta\]