# 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 jac – The derivative of the loglikelihood for each observation evaluated at params. array-like

Notes

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

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