class statsmodels.discrete.discrete_model.MultinomialModel(endog, exog, **kwargs)[source]


cdf(X) The cumulative distribution function of the model.
cov_params_func_l1(likelihood_model, xopt, …) Computes cov_params on a reduced parameter space corresponding to the nonzero parameters resulting from the l1 regularized fit.
fit([start_params, method, maxiter, …]) Fit the model using maximum likelihood.
fit_regularized([start_params, method, …]) Fit the model using a regularized maximum likelihood.
from_formula(formula, data[, subset, drop_cols]) Create a Model from a formula and dataframe.
hessian(params) The Hessian matrix of the model
information(params) Fisher information matrix of model
initialize() Preprocesses the data for MNLogit.
loglike(params) Log-likelihood of model.
pdf(X) The probability density (mass) function of the model.
predict(params[, exog, linear]) Predict response variable of a model given exogenous variables.
score(params) Score vector of model.


endog_names Names of endogenous variables
exog_names Names of exogenous variables