A class of continuous bivariate distributions with linear sum of hazard gradient components

Jayme Pinto () and Nikolai Kolev ()
Additional contact information
Jayme Pinto: University of São Paulo
Nikolai Kolev: University of São Paulo

Journal of Statistical Distributions and Applications, 2016, vol. 3, issue 1, 1-17

Abstract: Abstract The main purpose of this article is to characterize a class of bivariate continuous non-negative distributions such that the sum of the components of underlying hazard gradient vector is a linear function of its arguments. It happens that this class is a stronger version of the Sibuya-type bivariate lack of memory property. Such a class is allowed to have only certain marginal distributions and the corresponding restrictions are given in terms of marginal densities and hazard rates. We illustrate the methodology developed by examples, obtaining two extended versions of the bivariate Gumbel’s law.

Keywords: Bivariate hazard gradient; Bivariate lack of memory property; Characterization; Gumbel’s bivariate exponential; Marshall-Olkin model; Sibuya’a dependence function; Primary: 62H05; 60E05 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1186/s40488-016-0048-x Abstract (text/html)

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:jstada:v:3:y:2016:i:1:d:10.1186_s40488-016-0048-x

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/40488

DOI: 10.1186/s40488-016-0048-x

Access Statistics for this article

Journal of Statistical Distributions and Applications is currently edited by Felix Famoye and Carl Lee

More articles in Journal of Statistical Distributions and Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().