statsmodels.discrete.discrete_model.Logit.score_obs¶

Logit.score_obs(params)[source]¶

Logit model Jacobian of the log-likelihood for each observation

Parameters:

params: array-like

The parameters of the model

Returns:

jac : ndarray, (nobs, k_vars)

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

Notes

$\frac{\partial\ln L_{i}}{\partial\beta}=\left(y_{i}-\Lambda_{i}\right)x_{i}$

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