Probit.score()
statsmodels.discrete.discrete_model.Probit.score
-
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.
© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.discrete.discrete_model.Probit.score.html