Logit model score (gradient) vector of the log-likelihood
params: array-like :
The parameters of the model
score : ndarray, 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}
statsmodels.discrete.discrete_model.Logit.predict
statsmodels.discrete.discrete_model.Probit
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