On moments of folded and truncated multivariate Student-t distributions based on recurrence relations

Christian E. Galarza, Tsung-I Lin, Wan-Lun Wang and Víctor H. Lachos ()
Additional contact information
Christian E. Galarza: Escuela Superior Politécnica del Litoral, ESPOL
Tsung-I Lin: National Chung Hsing University
Wan-Lun Wang: Feng Chia University
Víctor H. Lachos: University of Connecticut

Metrika: International Journal for Theoretical and Applied Statistics, 2021, vol. 84, issue 6, No 2, 825-850

Abstract: Abstract The use of the first two moments of the truncated multivariate Student-t distribution has attracted increasing attention from a wide range of applications. This paper develops recurrence relations for integrals that involve the density of multivariate Student-t distributions. The proposed techniques allow for fast computation of arbitrary-order product moments of folded and truncated multivariate Student-t distributions and offer explicit expressions of low-order moments of folded and truncated multivariate Student-t distributions. A real data example containing positive censored responses is applied to illustrate the effectiveness and importance of the proposed methods. An R MomTrunc package is developed and publicly available on the CRAN repository.

Keywords: EM algorithm; Folded multivariate Student-t distribution; Product moments; Truncated multivariate normal distribution; Truncated multivariate Student-t distribution (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://link.springer.com/10.1007/s00184-020-00802-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:metrik:v:84:y:2021:i:6:d:10.1007_s00184-020-00802-1

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/184/PS2

DOI: 10.1007/s00184-020-00802-1

Access Statistics for this article

Metrika: International Journal for Theoretical and Applied Statistics is currently edited by U. Kamps and Norbert Henze

More articles in Metrika: International Journal for Theoretical and Applied Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().