statsmodels.discrete.discrete_model.Logit.score_obs

Logit.score_obs(params)

Logit model Jacobian of the log-likelihood for each observation

Parameters:

paramsarray_like

The parameters of the model

Returns:

jacarray_like

The derivative of the loglikelihood for each observation evaluated at params.

Notes

$$\frac{\partial \ln L_i}{\partial \beta }=(y_i-{\mathrm{\Lambda }}_i)x_i$$

for observations $i=1,...,n$