Implementing likelihood-based inference for fat-tailed distributions

The theoretical advancements in higher-order likelihood-based inference methods have been tremendous over the past two decades. The application of these methods in the applied literature however has been far from widespread. A critical barrier to adoption has likely been the computational difficulties associated with the implementation of these methods. This paper provides the applied researcher with a systematic exposition of the calculations and computer code required to implement the higher-order conditional inference methodology of Fraser and Reid [1995. Utilitas Mathematica 47, 33-53] for problems involving heavy- or fat-tailed distributions.