statsmodels.discrete.conditional_models.ConditionalMNLogit¶
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class
statsmodels.discrete.conditional_models.
ConditionalMNLogit
(endog, exog, missing='none', **kwargs)[source]¶ Fit a conditional multinomial logit model to grouped data.
Parameters: endog : array-like
The dependent variable, must be integer-valued, coded 0, 1, …, c-1, where c is the number of response categories.
exog : array-like
The independent variables.
groups : array-like
Codes defining the groups. This is a required keyword parameter.
Notes
Equivalent to femlogit in Stata.
References
Gary Chamberlain (1980). Analysis of covariance with qualitative data. The Review of Economic Studies. Vol. 47, No. 1, pp. 225-238.
Attributes
endog_names
Names of endogenous variables exog_names
Names of exogenous variables Methods
fit
([start_params, method, maxiter, …])Fit method for likelihood based models fit_regularized
([method, alpha, …])Return a regularized fit to a linear regression model. 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
()Initialize (possibly re-initialize) a Model instance. loglike
(params)Log-likelihood of model. predict
(params[, exog])After a model has been fit predict returns the fitted values. score
(params)Score vector of model.