Log-likelihood of the multinomial logit model.
Parameters: | params : array-like
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Returns: | loglike : float
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Notes
\ln L=\sum_{i=1}^{n}\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)
where d_{ij}=1 if individual i chose alternative j and 0 if not.