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Multivariate L ‐moment homogeneity test
Author(s) -
Chebana F.,
Ouarda T. B. M. J.
Publication year - 2007
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1029/2006wr005639
Subject(s) - multivariate statistics , gumbel distribution , homogeneity (statistics) , copula (linguistics) , bivariate analysis , statistics , mathematics , econometrics , multivariate analysis , flood myth , logistic regression , marginal distribution , statistical hypothesis testing , univariate , random variable , extreme value theory , geography , archaeology
Several types of hydrological events are described with multivariate characteristics (droughts, floods, rain storms, etc.). When carrying out a multivariate regional frequency analysis for these events it is important to jointly consider all these characteristics. The aim of this paper is to extend the statistical homogeneity test of Hosking and Wallis (1993) to the multivariate case. As a tool, multivariate L ‐moments are used to define the statistics and general copula models to describe the statistical behavior of dependent variables. The usefulness of the methodology is illustrated on flood events. Monte‐Carlo simulations are also performed for a bivariate Gumbel logistic model with Gumbel marginal distributions. Results illustrate the power of the proposed multivariate L ‐moment homogeneity test to detect heterogeneity on the whole structure of the model and on the marginal distributions. In a bivariate flood setting, a comparison is carried out with the classical homogeneity test of Hosking and Wallis based on several types of regions.