statsmodels.discrete.discrete_model.Probit.score¶
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Probit.
score
(params)[source]¶ Probit model score (gradient) vector
Parameters: params : array-like
The parameters of the model
Returns: score : ndarray, 1-D
The score vector of the model, i.e. the first derivative of the loglikelihood function, evaluated at params
Notes
Where . This simplification comes from the fact that the normal distribution is symmetric.