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Robust Likelihood Methods Based on the Skew-"t" and Related Distributions

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  • Adelchi Azzalini
  • Marc G. Genton

Abstract

The robustness problem is tackled by adopting a parametric class of distributions flexible enough to match the behaviour of the observed data. In a variety of practical cases, one reasonable option is to consider distributions which include parameters to regulate their skewness and kurtosis. As a specific representative of this approach, the skew-"t" distribution is explored in more detail and reasons are given to adopt this option as a sensible general-purpose compromise between robustness and simplicity, both of treatment and of interpretation of the outcome. Some theoretical arguments, outcomes of a few simulation experiments and various wide-ranging examples with real data are provided in support of the claim. Copyright 2007 The Authors. Journal compilation (c) 2007 International Statistical Institute.

Suggested Citation

  • Adelchi Azzalini & Marc G. Genton, 2008. "Robust Likelihood Methods Based on the Skew-"t" and Related Distributions," International Statistical Review, International Statistical Institute, vol. 76(1), pages 106-129, April.
  • Handle: RePEc:bla:istatr:v:76:y:2008:i:1:p:106-129
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