The classical multivariate Pareto model, which was referred to by Arnold [Arnold, B.C., 1983. Pareto Distributions. International Co-operative Publishing House], and is used to fit heavy tailed random variables, has serious disadvantages. First, each of its marginals has the same distribution up to location and scale parameters. Secondly, this model has a rigid dependence structure. Furthermore, the independent Pareto marginals do not belong to this model. In this paper, we introduce two multivariate models, whose marginals have different shape parameters and a more flexible dependence structure. Moreover, the independent Pareto marginals model is a special case of one of the suggested models. We also discuss regression and a measure of dependence for these models, along with some relevant inferences. The paper concludes with a numerical study.
Download Info
To download:
If you experience problems downloading a file, check if you have the
proper application to
view it first. Information about this may be contained
in the File-Format links below. In case of further problems read
the IDEAS help
page. Note that these files are not on the IDEAS
site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 79 (2009) Issue (Month): 16 (August) Pages: 1733-1743 Download reference. The following formats are available: HTML
(with abstract),
plain text
(with abstract),
BibTeX,
RIS (EndNote, RefMan, ProCite),
ReDIF