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- Title
Robust Likelihood Methods Based on the Skew- t and Related Distributions.
- Authors
Azzalini, Adelchi; Genton, Marc G.
- 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.
- Subjects
MAXIMUM likelihood statistics; MULTIVARIATE analysis; ROBUST statistics; DISTRIBUTION (Probability theory); DISTRIBUTED parameter systems
- Publication
International Statistical Review, 2008, Vol 76, Issue 1, p106
- ISSN
0306-7734
- Publication type
Article
- DOI
10.1111/j.1751-5823.2007.00016.x