PAS method estimates extreme non-linear wave impact loads within 2-15% of brute-force Monte Carlo results while using only 1-3% of the high-fidelity simulation time.
4 Noel Cressie.Statistics for spatial data
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
A hierarchical model with bivariate GEV distributions and intrinsic CAR spatial structure attributes causal effects of anthropogenic forcing on annual temperature maxima return levels using CMIP6 factual and counterfactual simulations.
A bilinear extreme spatial model for multi-output aircraft production data that captures extremal dependence via graph-assisted composite likelihood estimation and shows better extreme-event prediction than standard methods.
citing papers explorer
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Design loads for wave impacts -- introducing the Probabilistic Adaptive Screening (PAS) method for predicting extreme non-linear loads on maritime structures
PAS method estimates extreme non-linear wave impact loads within 2-15% of brute-force Monte Carlo results while using only 1-3% of the high-fidelity simulation time.
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Estimating Causal Attribution of Anthropogenic Forcing on High-Temperature Extremes Using a Latent Gaussian Spatial Model
A hierarchical model with bivariate GEV distributions and intrinsic CAR spatial structure attributes causal effects of anthropogenic forcing on annual temperature maxima return levels using CMIP6 factual and counterfactual simulations.
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Multi-output Extreme Spatial Model for Complex Aircraft Production Systems
A bilinear extreme spatial model for multi-output aircraft production data that captures extremal dependence via graph-assisted composite likelihood estimation and shows better extreme-event prediction than standard methods.