statsmodels.discrete.discrete_model.Logit.score¶

Logit.score(params)[source]¶

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

Parameters:¶

paramsarray_like

The parameters of the model

Returns:¶

scorendarray, 1-D

The score vector of the model, i.e. the first derivative of the loglikelihood function, evaluated at params

Notes

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