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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

Returns:

score : ndarray (nobs, k_vars)

The score vector 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

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