'Log-likelihood of the multinomial logit model for each observation.
Parameters
params : array-like
The parameters of the multinomial logit model.
Returns
loglike : array-like
The log likelihood for each observation of the model evaluated
at `params`. See Notes
Notes
.. math:: \ln L_{i}=\sum_{j=0}^{J}d_{ij}\ln\left(\frac{\exp\left(\beta_{j}^{\prime}x_{i}\right)}{\sum_{k=0}^{J}\exp\left(\beta_{k}^{\prime}x_{i}\right)}\right)
for observations :math:`i=1,...,n`
where :math:`d_{ij}=1` if individual `i` chose alternative `j` and 0
if not.'

def loglikeobs(self, params):

    params = params.reshape(self.K, (-1), order='F')
    d = self.wendog
    logprob = np.log(self.cdf(np.dot(self.exog, params)))
    return (d * logprob)
