statsmodels.discrete.conditional_models.ConditionalMNLogit¶
-
class
statsmodels.discrete.conditional_models.
ConditionalMNLogit
(endog, exog, missing='none', **kwargs)[source]¶ Fit a conditional multinomial logit model to grouped data.
- Parameters
- endogarray_like
The dependent variable, must be integer-valued, coded 0, 1, …, c-1, where c is the number of response categories.
- exogarray_like
The independent variables.
- groupsarray_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.
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 (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.
Properties
Names of endogenous variables.
Names of exogenous variables.