Loglikelihood of linear model with t distributed errors.
Parameters: | params : array
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Returns: | loglike : array, (nobs,)
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Notes
\ln L=\sum_{i=1}^{n}\left[-\lambda_{i}+y_{i}x_{i}^{\prime}\beta-\ln y_{i}!\right]
The t distribution is the standard t distribution and not a standardized t distribution, which means that the scale parameter is not equal to the standard deviation.
self.fixed_params and self.expandparams can be used to fix some parameters. (I doubt this has been tested in this model.)