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# scikits.statsmodels.discretemod.MNLogit.hessian

`MNLogit.``hessian`(params)

  > Multinomial logit Hessian matrix of the log-likelihood

  Parameters: | params : array-like The parameters of the model
  Returns: | The Hessian evaluated at `params` :

  ight)` equals 1 if j = l and 0

    otherwise.

    The actual Hessian matrix has J**2 * K x K elements. Our Hessian is reshaped to be square (J*K, J*K) so that the solvers can use it.

    This implementation does not take advantage of the symmetry of the Hessian and could probably be refactored for speed.

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