statsmodels.discrete.conditional_models.ConditionalMNLogit

class statsmodels.discrete.conditional_models.ConditionalMNLogit(endog, exog, missing='none', **kwargs)

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.

missing{‘none’, ‘drop’, ‘raise’}, optional

If ‘none’, no nan checking is done. If ‘drop’, any observations with nans are dropped. If ‘raise’, an error is raised.

Attributes:

endog_names

Names of endogenous variables

exog_names

Names of exogenous variables

Methods

fit([start_params, method, maxiter, ...])	Fit the conditional multinomial logit model.
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)	Returns numerical approximation to the Hessian.
information(params)	Fisher information matrix of model
initialize()	Initialize (possibly re-initialize) a Model instance
loglike(params)	Log-likelihood of the conditional multinomial logit model.
predict(params[, exog])	After a model has been fit, predict returns the fitted values
score(params)	Score vector of the conditional multinomial logit model.

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 the conditional multinomial logit model.
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)	Returns numerical approximation to the Hessian.
information(params)	Fisher information matrix of model
initialize()	Initialize (possibly re-initialize) a Model instance
loglike(params)	Log-likelihood of the conditional multinomial logit model.
predict(params[, exog])	After a model has been fit, predict returns the fitted values
score(params)	Score vector of the conditional multinomial logit model.

Properties

endog_names	Names of endogenous variables
exog_names	Names of exogenous variables