Testing for Normality When the Sampled Distribution Is Extended Skew-Normal

Cinzia Franceschini () and Nicola Loperfido ()
Additional contact information
Cinzia Franceschini: Università degli Studi di Urbino “Carlo Bo”, Facoltà di Giurisprudenza
Nicola Loperfido: Università degli Studi di Urbino “Carlo Bo”, Dipartimento di Economia, Società e Politica

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2014, pp 159-169 from Springer

Abstract: Abstract The extended skew-normal (ESN) distribution includes the normal one as a special case. Unfortunately, its information matrix is singular under normality, thus preventing application of standard likelihood-based methods for testing the null hypothesis of normality. The paper shows that for univariate ESN distributions the sample skewness provides the locally most powerful test for normality among the location and scale invariant ones. The generalization to multivariate ESN distributions considers projections of the data onto the direction corresponding to maximal skewness. Related computational problems simplifies for the multivariate ESN distribution, where the direction maximizing skewness is shown to have a simple parametric interpretation.

Keywords: Information Matrix; Multivariate Normality; Stochastic Frontier Analysis; Closing Price; Projection Pursuit (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:sprchp:978-3-319-02499-8_15

Ordering information: This item can be ordered from
http://www.springer.com/9783319024998

DOI: 10.1007/978-3-319-02499-8_15

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().