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statsmodels.discrete.discrete_model.MultinomialModel

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

Methods

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]) 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.

Attributes

endog_names
exog_names

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