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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
Returns: score – The score vector of the model, i.e. the first derivative of the loglikelihood function, evaluated at params
Return type: ndarray, 1-D

Notes

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

© 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.Logit.score.html