Inference and further probabilistic properties of the $$ SUN_{n,2}$$ S U N n, 2 -distribution

Mehdi Amiri (), Ahad Jamalizadeh () and Mina Towhidi ()

Statistical Papers, 2015, vol. 56, issue 4, 1098 pages

Abstract: In this paper the normal-skew-normal distribution, proposed by Gomez et al. (Statistics 47:411–421, 2013 ), is extended to the multivariate case. It is also a special case of $$SUN_{n,2}$$ S U N n , 2 -distribution, recently studied by Arellano-Valle and Genton (Chil J Stat 2:17–34, 2010 ). We show that the proposed distribution can be expressed as a shape mixture of the multivariate extended skew-normal distribution. Applying this property leads to deriving stochastic representations for the proposed distribution. Also we give some basic properties for this new family. Computational techniques using EM-type algorithms are employed for iteratively computing maximum likelihood estimates. Finally, an application of the new distribution is illustrated using some real data sets. Copyright Springer-Verlag Berlin Heidelberg 2015

Keywords: Multivariate normal-skew-normal distribution; Multivariate SUN distribution; Shape mixture; Skewness; EM-type algorithm; Maximum likelihood estimation (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1007/s00362-014-0625-3 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:stpapr:v:56:y:2015:i:4:p:1071-1098

Ordering information: This journal article can be ordered from
http://www.springer. ... business/journal/362

DOI: 10.1007/s00362-014-0625-3

Access Statistics for this article

Statistical Papers is currently edited by C. Müller, W. Krämer and W.G. Müller

More articles in Statistical Papers from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().