Login Register

MultinomialModel.information()

statsmodels.discrete.discrete_model.MultinomialModel.information

MultinomialModel.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.MultinomialModel.information.html

doc_statsmodels

2025-01-10 15:47:30

Comments

Leave a Comment

Please login to continue.

Popular Articles

MultinomialModel.predict() statsmodels.discrete.discrete_model.MultinomialModel.predict MultinomialModel.predict(params, exog=None, linear=False) [source] Predict response v

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

MultinomialModel.cdf() statsmodels.discrete.discrete_model.MultinomialModel.cdf MultinomialModel.cdf(X) The cumulative distribution function of the model.

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

MultinomialModel.initialize() statsmodels.discrete.discrete_model.MultinomialModel.initialize MultinomialModel.initialize() [source] Preprocesses the data for MNLogit.