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Robust Likelihood Methods Based on the Skew‐ t and Related Distributions
Author(s) -
Azzalini Adelchi,
Genton Marc G.
Publication year - 2008
Publication title -
international statistical review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.051
H-Index - 54
eISSN - 1751-5823
pISSN - 0306-7734
DOI - 10.1111/j.1751-5823.2007.00016.x
Subject(s) - skew , skewness , kurtosis , robustness (evolution) , parametric statistics , computer science , econometrics , compromise , simplicity , mathematical optimization , mathematics , statistics , telecommunications , social science , biochemistry , chemistry , philosophy , epistemology , sociology , gene
Summary 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.