# statsmodels.discrete.discrete_model.Logit.score¶

Logit.score(params)[source]

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

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

Notes

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