Exploiting occurrence times in likelihood inference for componentwise maxima

By Alec Stephenson, Jonathan A. Tawn. 2005

69 citations recorded by the source corpus.

Subfields: Finance, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/52598e3d2a23fd15fa0d71c951d75bc25798d706

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Citations in the corpus

Efficient inference and simulation for elliptical Pareto processes (2013, background): “Wadsworth & Tawn (2013) show that a likelihood based on componentwise maxima and their occurrence times (Stephenson & Tawn, 2005) represents a special case of the point process approach.”
Likelihood estimators for multivariate extremes (2014, methodology): “In order to increase computational and statistical efficiency, Stephenson and Tawn (2005) proposed a refined approach which uses the extra information of occurrence times of extreme events, a biased-corrected version of which is proposed by Wadsworth (2015).”
Spatial modeling of extreme snow depth (2011, methodology): “Geometric anisotropy as induced by the V matrix is a special case of range anisotropy [Zimmerman (1993)].”
Non-Stationary Dependence Structures for Spatial Extremes (2014, background): “However, more efficient approaches based on full likelihoods (Stephenson and Tawn, 2005; Wadsworth and Tawn, 2014; Thibaud and Opitz, 2014) might be devised for the extremal t model.”
Geostatistics of extremes (2012, background): “In this case, arguments of Stephenson & Tawn (2005) show that if the maxima at the two sites are known to occur simultaneously, then the likelihood contribution should be fsim(z1, z2) = −v 2V (z1, z2) vz1vz2 exp{−V (z1, z2)}, z1, z2 > 0, (3.2) whereas if they are known to occur at different times,…”
Geostatistics of Dependent and Asymptotically Independent Extremes (2013, background): “Furthermore, following Stephenson and Tawn (2005), Davison and Gholamrezaee (2012) and Wadsworth and Tawn (2013) show how to incorporate the occurrence times of extreme events, use of which both simplifies the likelihood and allows much more efficient inference in cases of moderate to low spatial…”
Modeling Spatial Processes with Unknown Extremal Dependence Class (2017, background): “Wadsworth and Tawn (2014) simplified the likelihood by conditioning on event times (Stephenson and Tawn, 2005), although Wadsworth (2015) and Huser et al.”