Pages that link to "Item:Q5857128"

The following pages link to A Hierarchical Max-Infinitely Divisible Spatial Model for Extreme Precipitation (Q5857128):

Displaying 21 items.

• A comparison study of extreme precipitation from six different regional climate models via spatial hierarchical modeling (Q549647) (← links)
• Geoadditive modeling for extreme rainfall data (Q1621237) (← links)
• The MELBS team winning entry for the EVA2017 competition for spatiotemporal prediction of extreme rainfall using generalized extreme value quantiles (Q1792637) (← links)
• Exact simulation of continuous max-id processes with applications to exchangeable max-id sequences (Q2101467) (← links)
• Modeling spatial tail dependence with Cauchy convolution processes (Q2106793) (← links)
• Modeling nonstationary temperature maxima based on extremal dependence changing with event magnitude (Q2135353) (← links)
• Approximate Bayesian inference for analysis of spatiotemporal flood frequency data (Q2154186) (← links)
• Estimating high-resolution red sea surface temperature hotspots, using a low-rank semiparametric spatial model (Q2245130) (← links)
• A hierarchical model for the analysis of spatial rainfall extremes (Q2259827) (← links)
• New exploratory tools for extremal dependence: \(\chi \) networks and annual extremal networks (Q2273002) (← links)
• Exchangeable min-id sequences: characterization, exponent measures and non-decreasing id-processes (Q2688196) (← links)
• Tail and quantile estimation for real-valued \(\beta\)-mixing spatial data (Q2693222) (← links)
• Flexible and Fast Spatial Return Level Estimation Via a Spatially Fused Penalty (Q5066495) (← links)
• Local Likelihood Estimation of Complex Tail Dependence Structures, Applied to U.S. Precipitation Extremes (Q5120643) (← links)
• Multivariate extremes and max-stable processes: discussion of the paper by Zhengjun Zhang (Q5880060) (← links)
• Computationally efficient spatial modeling of annual maximum 24‐h precipitation on a fine grid (Q6139151) (← links)
• Advances in statistical modeling of spatial extremes (Q6602343) (← links)
• Transformed-linear models for time series extremes (Q6604023) (← links)
• A hierarchical Bayesian non-asymptotic extreme value model for spatial data (Q6626619) (← links)
• An extended PDE-based statistical spatio-temporal model that suppresses the Gibbs phenomenon (Q6626646) (← links)
• Partial Tail-Correlation Coefficient Applied to Extremal-Network Learning (Q6637459) (← links)