Balakrishnan Skew-t Distribution and Associated Statistical Characteristics

S. Shafiei and M. Doostparast

Communications in Statistics - Theory and Methods, 2014, vol. 43, issue 19, 4109-4122

Abstract: As a discussant of Arnold and Beaver (2002), Balakrishnan proposed a generalized skew-normal (BSN) distribution. This new model has been encountered in the literature for modeling various data sets. In this paper, we propose a new generalization of skew t-distribution of Azzalini and Capitanio (2003), denoted by BST$\textit{BST}$, as a scale mixture of the BSN-distribution. This new model may be used for modeling data sets exhibiting a unimodal density function having some skewness as well as heavy tails with respect to the skew-normal distribution. An explicit expression for the probability density function and a recurrence formula for the cumulative distribution function of the BST$\textit{BST}$-distribution are derived. Some statistical characteristics of the proposed model including central moments, unimodality, and stochastic orders are investigated. Two representation theorems for BST$\textit{BST}$-distribution which may be used for generating copies from the new model are given. The problem of estimation of the unknown parameters on the basis of a random sample arising from BST$\textit{BST}$-distribution is considered. For illustration proposes, a real data set on strength of glass fibers, due to Smith and Naylor (1987), is analyzed using the procedures obtained.

Date: 2014
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2012.701697 (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:taf:lstaxx:v:43:y:2014:i:19:p:4109-4122

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2012.701697

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().