Multivariate Weibull and Pareto Distributions in Hilbert Space

Hsiaw-Chan Yeh

Communications in Statistics - Theory and Methods, 2015, vol. 44, issue 14, 3073-3086

Abstract: Two general multivariate distributions in a real separable Hilbert space H are introduced in this article, one is multivariate Weibull distribution (denoted by GMWH), the other is multivariate Pareto distribution (denoted by GMPH). They are more general than the existing references. Some characterization theorems of the GMWH and GMPH via an intensively monotone operator are proved. The limiting behaviors and the interrelationship between the GMW and GMP in Euclidean space are also studied.

Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2013.809119 (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:44:y:2015:i:14:p:3073-3086

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

DOI: 10.1080/03610926.2013.809119

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 ().