Login Register

BinaryModel.information()

statsmodels.discrete.discrete_model.BinaryModel.information

BinaryModel.information(params)

Fisher information matrix of model

Returns -Hessian of loglike evaluated at params.

Links:

http://statsmodels.sourceforge.net/stable/generated/statsmodels.discrete.discrete_model.BinaryModel.information.html

doc_statsmodels

2017-01-18 16:07:19

Comments

Leave a Comment

Please login to continue.

Popular Articles

BinaryModel.fit() statsmodels.discrete.discrete_model.BinaryModel.fit BinaryModel.fit(start_params=None, method='newton', maxiter=35, full_output=1, disp=1, callback=

BinaryModel.loglike() statsmodels.discrete.discrete_model.BinaryModel.loglike BinaryModel.loglike(params) Log-likelihood of model.

BinaryModel.pdf() statsmodels.discrete.discrete_model.BinaryModel.pdf BinaryModel.pdf(X) The probability density (mass) function of the model.

BinaryModel.hessian() statsmodels.discrete.discrete_model.BinaryModel.hessian BinaryModel.hessian(params) The Hessian matrix of the model

BinaryModel.predict() statsmodels.discrete.discrete_model.BinaryModel.predict BinaryModel.predict(params, exog=None, linear=False) [source] Predict response variable of