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Flexible Distributions as an Approach to Robustness: The Skew-t Case

In: Recent Advances in Robust Statistics: Theory and Applications

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  • Adelchi Azzalini

    (University of Padua, Department of Statistical Sciences)

Abstract

The use of flexible distributions with adaptive tails as a route to robustness has a long tradition. Recent developments in distribution theory, especially of non-symmetric form, provide additional tools for this purpose. We discuss merits and limitations of this approach to robustness as compared with classical methodology. Operationally, we adopt the skew-t as the working family of distributions used to implement this line of thinking.

Suggested Citation

  • Adelchi Azzalini, 2016. "Flexible Distributions as an Approach to Robustness: The Skew-t Case," Springer Books, in: Claudio Agostinelli & Ayanendranath Basu & Peter Filzmoser & Diganta Mukherjee (ed.), Recent Advances in Robust Statistics: Theory and Applications, pages 1-16, Springer.
    • Handle: RePEc:spr:sprchp:978-81-322-3643-6_1
    DOI: 10.1007/978-81-322-3643-6_1
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