Exact confidence sets and goodness-of-fit methods for stable distributions

  title={Exact confidence sets and goodness-of-fit methods for stable distributions},
  author={Marie-Claude Beaulieu and Universit́e Laval and Jean-Marie Dufour},
Usual inference methods for stable distributions are typically based on limit dis tributions. But asymptotic approximations can easily be unreliable in such cases, for standa rd regularity conditions may not apply or may hold only weakly. This paper proposes finite-sample tes ts and confidence sets for tail thickness and asymmetry parameters ( α andβ ) of stable distributions. The confidence sets are built by inverting exact goodness-of-fit tests for hypotheses whic h assign specific values to… CONTINUE READING


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