Loglikelihood of linear model with t distributed errors.

Parameters:params (array) – The parameters of the model. The last 2 parameters are degrees of freedom and scale.
Returns:loglike – The log likelihood of the model evaluated at params for each observation defined by self.endog and self.exog.
Return type:array


\[\ln L=\sum_{i=1}^{n}\left[-\lambda_{i}+y_{i}x_{i}^{\prime}\beta-\ln y_{i}!\right]\]

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.)