statsmodels.discrete.discrete_model.Logit.score

Logit.score(params)

Logit model score (gradient) vector of the log-likelihood

Parameters:params (array-like) – The parameters of the model Returns:score – The score vector of the model, i.e. the first derivative of the loglikelihood function, evaluated at params Return type:ndarray, 1-D

Notes

$$\frac{\partial\ln L}{\partial\beta}=\sum_{i=1}^{n}\left(y_{i}-\Lambda_{i}\right)x_{i}$$