Results 21 to 30 of about 136,797 (255)
Revstat Statistical Journal, 2012 We survey the current practice of analyzing spatial extreme data, which lies at the intersection of extreme value theory and geostatistics. Characterizations of multivariate max-stable distributions typically assume specific univariate marginal ...
Daniel Cooley +6 more
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Tail correlation functions of max-stable processes [PDF]
Extremes, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Strokorb, Kirstin +2 more
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Plants, 2021 Macroautophagy/autophagy is a fundamental catabolic pathway that maintains cellular homeostasis in eukaryotic cells by forming double-membrane-bound vesicles named autophagosomes.
Elsa-Herminia Quezada-Rodríguez +5 more
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Multivariate max-stable spatial processes [PDF]
Biometrika, 2015 SUMMARY Max-stable processes allow the spatial dependence of extremes to be modelled and quantified, so they are widely adopted in applications. For a better understanding of extremes, it may be useful to study several variables simultaneously. To this end, we study the maxima of independent replicates of multivariate processes, both in the Gaussian ...
Genton, Marc G. +2 more
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A Comparative Tour through the Simulation Algorithms for Max-Stable Processes [PDF]
Statistical Science, 2022 Being the max-analogue of $α$-stable stochastic processes, max-stable processes form one of the fundamental classes of stochastic processes. With the arrival of sufficient computational capabilities, they have become a benchmark in the analysis of spatio-temporal extreme events.
Oesting, Marco, Strokorb, Kirstin
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A max-stable process model for rainfall extremes at different accumulation durations
Weather and Climate Extremes, 2016 A common existing approach to modeling rainfall extremes employs a spatial Bayesian hierarchical model, where latent Gaussian processes are specified on distributional parameters in order to pool spatial information.
Alec G. Stephenson +2 more
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Marginal standardization of upper semicontinuous processes. With application to max-stable processes [PDF]
Journal of Applied Probability, 2017 Abstract Extreme value theory for random vectors and stochastic processes with continuous trajectories is usually formulated for random objects where the univariate marginal distributions are identical. In the spirit of Sklar's theorem from copula theory, such marginal standardization is carried out by the pointwise probability integral transform ...
Sabourin, Anne, Segers, Johan
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Pharmaceutics, 2023 Despite intensive monitoring of whole blood tacrolimus concentrations, acute rejection after kidney transplantation occurs during tacrolimus therapy.
Pere Fontova +15 more
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Variational inference for max-stable processes
, 2022 Max-stable processes provide natural models for the modelling of spatial extreme values observed at a set of spatial sites. Full likelihood inference for max-stable data is, however, complicated by the form of the likelihood function as it contains a sum over all partitions of sites.
Andersson, Patrik, Engberg, Alexander
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An extended sparse max-linear moving model with application to high-frequency financial data
Statistical Theory and Related Fields, 2017 There continues to be unfading interest in developing parametric max-stable processes for modelling tail dependencies and clustered extremes in time series data.
Timothy Idowu, Zhengjun Zhang
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