@article{fdi:010080895,
  title = {{E}xtra-parametrized extreme value copula : extension to a spatial framework},
  author = {{C}arreau, {J}ulie and {T}oulemonde, {G}.},
  editor = {},
  language = {{ENG}},
  abstract = {{H}azard assessment at a regional scale may be performed thanks to a spatial model for maxima that can be obtained by combining the generalized extreme-value ({GEV}) distribution for the univariate marginal distributions with extreme-value copulas to describe their dependence structure, as justified by the theory of multivariate extreme values. {A} flexible class of extreme-value copulas, called {XG}umbel for short, combines two {G}umbel copulas with extra-parameters weighting each dimension. {I}n a multisite study, the {XG}umbel copula quickly becomes over-parametrized. {I}n addition, interpolation to ungauged locations is not easily achieved. {W}e develop an extension of the {XG}umbel copula to the spatial framework by defining the extra-parameters as a mapping shaped as a disk. {T}he inference of the {S}patialized {XG}umbel copula is performed thanks to an {A}pproximate {B}ayesian {C}omputation ({ABC}) scheme with summary statistics based on upper tail dependence coefficients. {T}he {GEV} parameters are estimated with a spatial regression model built with a vector generalized linear model. {W}e evaluate and compare this spatial model with the {B}rown-{R}esnick process on annual maxima of daily precipitation totals at 177 gauged stations in the {F}rench {M}editerranean over a 57 year period. {O}ur analyses show that the {ABC} scheme yields, except in one instance, interpretable parameters. {I}n addition, the {S}patialized {XG}umbel copula is able to reproduce reasonably well the non-stationarity present in our case study.},
  keywords = {{G}umbel copula ; {S}patial extremes ; {H}eavy precipitation ; {ABC} ; {N}on-stationarity ; {FRANCE} ; {ZONE} {MEDITERRANEENNE}},
  booktitle = {},
  journal = {{S}patial {S}tatistics},
  volume = {40},
  numero = {no sp{\'e}cial},
  pages = {100410 [20 ]},
  ISSN = {2211-6753},
  year = {2020},
  DOI = {10.1016/j.spasta.2020.100410},
  URL = {https://www.documentation.ird.fr/hor/fdi:010080895},
}