Results 31 to 40 of about 829,338 (182)
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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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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Max-infinitely divisible models and inference for spatial extremes
, 2020 For many environmental processes, recent studies have shown that the dependence strength is decreasing when quantile levels increase. This implies that the popular max-stable models are inadequate to capture the rate of joint tail decay, and to estimate ...
Huser, Raphael +2 more
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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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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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Long Range Dependence for Stable Random Processes
, 2020 We investigate long and short memory in $\alpha$-stable moving averages and max-stable processes with $\alpha$-Fr\'echet marginal distributions. As these processes are heavy-tailed, we rely on the notion of long range dependence suggested by Kulik and ...
Makogin, Vitalii +3 more
core +1 more source
A comparative tour through the simulation algorithms for max-stable processes [PDF]
, 2019 Being the max-analogue of $\alpha$-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 ...
Oesting, Marco, Strokorb, Kirstin
core +2 more sources
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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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
openaire +5 more sources
Analysis of Random Fields Using CompRandFld
Journal of Statistical Software, 2015 Statistical analysis based on random fields has become a widely used approach in order to better understand real processes in many fields such as engineering, environmental sciences, etc.
Simone A. Padoan, Moreno Bevilacqua
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