The multivariate Gaussian tail model: an application to oceanographic data

By P. Bortot, Stuart Coles, Jonathan A. Tawn. 2000

85 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Oceanography

View Paper: https://www.semanticscholar.org/paper/3169117884db8afd02c8033c9d33db559c759147

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In Global and Planetary Change

In Oceanography

Citations in the corpus

Modeling asymptotically independent spatial extremes based on Laplace random fields (2015, methodology): “Known as Gaussian copula modeling (Davison et al., 2012), this approach has been explored by Bortot et al. (2000) for oceanographic data and by Renard and Lang (2007) for hydrological data, among others.”
Bayesian inference for long-term prediction of significant wave height (2007, methodology): “003 by, amongst others, Carter and Challenor (1981), Muir and El Shaarawi (1986), and more recently by Ferreira and Guedes Soares (1998), Guedes Soares and Scotto (2001), Winterstein et al.”
Extreme Value Dependence in Financial Markets: Diagnostics, Models, and Financial Implications (2004, background): “Pr(Z > z) = Pr{min(S, T ) > z} = Pr(S > z, T > z) = L(z)z−1/η for z > u, (10)”
An application of Bayesian analysis and Markov chain Monte Carlo methods to the estimation of a regional trend in annual maxima (2006, background): “Although some promising approaches have been proposed [Coles and Tawn, 1990; Bortot et al., 2000; Favre et al., 2004], this aspect of the problem is beyond the scope of this paper. We thus make the hypothesis of independence between stations. As noted by Katz et al. [2002], this should have little e”
Use of a Gaussian copula for multivariate extreme value analysis: Some case studies in hydrology (2007, methodology): “For instance, Bortot et al. [3] reported empirical evidence of asymptotically independent data in the oceanographic field.”
A new class of models for bivariate joint tails (2009, methodology): “(1999), Bortot et al. (2000), Smith (2000), Coles and Pauli (2002), Sisson and Coles (2003) and Heffernan and Tawn (2004). The first reference to pinpoint and highlight the practical importance of this deficiency and to suggest an alternative framework for representing dependence in joint tails was ”
Modelling across extremal dependence classes (2014, methodology): “, filtered to correspond to a 15-hour time window for approximate temporal independence, and previously analyzed by Coles and Tawn (1994), Bortot et al. (2000) and Coles and Pauli (2002). Coles and Tawn (1994) noted the presence of seasonality, which was not taken into account in their, or subsequen”
Joint probability of precipitation and discharge deficits in the Netherlands (2004, methodology): “The inverse of the normal quantile transform has been used to obtain variables having marginal extreme value distributions and a multivariate normal dependence structure [Hosking and Wallis, 1988; Bortot et al., 2000].”
A conditional approach for multivariate extreme values (with discussion) (2004, background): “Ledford and Tawn (1996, 1997) proposed a bivariate threshold model to overcome this limitation, which has been explored and developed by Bortot and Tawn (1998), Peng (1999), Coles et al. (1999), Bortot et al. (2000), Heffernan (2000), Draisma et al. (2003) and Ledford and Tawn (2003).”
Space–time modelling of extreme events (2012, methodology): “(7) Different marginal thresholds could be used (Bortot et al., 2000) and the approach could be generalized to higher dimensions. However, in practice, the probability that an observed N -uplet falls into the “upper right quadrant” decays geometrically withN , leading to inference problems. In the n”