A robust factor analysis model using the restricted skew- $$t$$ t distribution

Tsung-I Lin (), Pal Wu, Geoffrey McLachlan () and Sharon Lee

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2015, vol. 24, issue 3, 510-531

Abstract: Factor analysis is a classical data-reduction technique that seeks a potentially lower number of unobserved variables that can account for the correlations among the observed variables. This paper presents an extension of the factor analysis model, called the skew- $$t$$ t factor analysis model, constructed by assuming a restricted version of the multivariate skew- $$t$$ t distribution for the latent factors and a symmetric $$t$$ t -distribution for the unobservable errors jointly. The proposed model shows robustness to violations of normality assumptions of the underlying latent factors and provides flexibility in capturing extra skewness as well as heavier tails of the observed data. A computationally feasible expectation conditional maximization algorithm is developed for computing maximum likelihood estimates of model parameters. The usefulness of the proposed methodology is illustrated using both simulated and real data. Copyright Sociedad de Estadística e Investigación Operativa 2015

Keywords: ECM algorithm; ML estimation; SNFA model; STFA model; rMSN distribution; rMST distribution; 62H12; 62H25 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
http://hdl.handle.net/10.1007/s11749-014-0422-2 (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:testjl:v:24:y:2015:i:3:p:510-531

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/11749/PS2

DOI: 10.1007/s11749-014-0422-2

Access Statistics for this article

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research is currently edited by Alfonso Gordaliza and Ana F. Militino

More articles in TEST: An Official Journal of the Spanish Society of Statistics and Operations Research from Springer, Sociedad de Estadística e Investigación Operativa
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().