  A decision must often be made between heavy-tailed and Gaussian errors for a
regression or a time series model, and the t-distribution is frequently used
when it is assumed that the errors are heavy-tailed distributed. The
performance of the likelihood ratio to choose between the two distributions is
investigated using entropy properties and a simulation study. The proportion of
times or probability that the likelihood of the correct assumption will be
bigger than the likelihood of the incorrect assumption is estimated.
