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# scikits.statsmodels.discretemod.MNLogit

class `scikits.statsmodels.discretemod.``MNLogit`(endog, exog=None)

  Multinomial logit model

  Parameters: | endog : array-like endog is an 1-d vector of the endogenous response. endog can contain strings, ints, or floats. Note that if it contains strings, every distinct string will be a category. No stripping of whitespace is done. exog : array-like exog is an n x p array where n is the number of observations and p is the number of regressors including the intercept if one is included in the data.

  Notes

  See developer notes for further information on MNLogit internals.

  Attributes

  Methods

  `cdf`(eXB) | Multinomial logit cumulative distribution function.
  `fit`([start_params, maxiter, method, tol]) | Fits the multinomial logit model.
  `hessian`(params) | Multinomial logit Hessian matrix of the log-likelihood
  `information`(params) | Fisher information matrix of model
  `initialize`() | Preprocesses the data for MNLogit.
  `loglike`(params) | Log-likelihood of the multinomial logit model.
  `pdf`(eXB) | NotImplemented
  `predict`(design) | After a model has been fit predict returns the fitted values.
  `score`(params) | Score matrix for multinomial logit model log-likelihood

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