Bayesian spatial clustering model for extremal hydrological variables integrating marginal tail similarity and spatial dependence to determine pooling levels.
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2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2019 2verdicts
UNVERDICTED 2representative citing papers
Applies PCA to re-scaled exceedances under regular variation and proves uniform convergence of empirical reconstruction risk plus consistency of the estimated optimal projection subspace.
citing papers explorer
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Bayesian spatial clustering of extremal behaviour for hydrological variables
Bayesian spatial clustering model for extremal hydrological variables integrating marginal tail similarity and spatial dependence to determine pooling levels.
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Principal Component Analysis for Multivariate Extremes
Applies PCA to re-scaled exceedances under regular variation and proves uniform convergence of empirical reconstruction risk plus consistency of the estimated optimal projection subspace.