The following pages link to Raphaël Huser (Q262537):
Displaying 40 items.
- Likelihood estimators for multivariate extremes (Q262538) (← links)
- Non-stationary dependence structures for spatial extremes (Q321454) (← links)
- (Q500743) (redirect page) (← links)
- Geostatistics of dependent and asymptotically independent extremes (Q500745) (← links)
- Hierarchical Archimax copulas (Q1661344) (← links)
- A comparison of dependence function estimators in multivariate extremes (Q1703851) (← links)
- INLA goes extreme: Bayesian tail regression for the estimation of high spatio-temporal quantiles (Q1792632) (← links)
- Max-and-smooth: a two-step approach for approximate Bayesian inference in latent Gaussian models (Q2057335) (← 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)
- Modeling spatial extremes using normal mean-variance mixtures (Q2135577) (← links)
- Approximate Bayesian inference for analysis of spatiotemporal flood frequency data (Q2154186) (← links)
- High-resolution Bayesian mapping of landslide hazard with unobserved trigger event (Q2170422) (← links)
- Asymmetric tail dependence modeling, with application to cryptocurrency market data (Q2170437) (← links)
- Estimating high-resolution red sea surface temperature hotspots, using a low-rank semiparametric spatial model (Q2245130) (← links)
- A spliced gamma-generalized Pareto model for short-term extreme wind speed probabilistic forecasting (Q2273005) (← links)
- Conex-connect: learning patterns in extremal brain connectivity from multichannel EEG data (Q2686027) (← links)
- Bayesian Model Averaging Over Tree-based Dependence Structures for Multivariate Extremes (Q3391465) (← links)
- Factor Copula Models for Replicated Spatial Data (Q4690973) (← links)
- Max‐infinitely divisible models and inference for spatial extremes (Q4994818) (← links)
- Space–Time Modelling of Extreme Events (Q5088227) (← links)
- Local Likelihood Estimation of Complex Tail Dependence Structures, Applied to U.S. Precipitation Extremes (Q5120643) (← links)
- Bayesian modeling of air pollution extremes using nested multivariate max‐stable processes (Q5214554) (← links)
- Modeling Spatial Processes with Unknown Extremal Dependence Class (Q5229925) (← links)
- Composite likelihood estimation for the Brown-Resnick process (Q5411052) (← links)
- A Hierarchical Max-Infinitely Divisible Spatial Model for Extreme Precipitation (Q5857128) (← links)
- Tractable Bayes of Skew-Elliptical Link Models for Correlated Binary Data (Q6055750) (← links)
- A combined statistical and machine learning approach for spatial prediction of extreme wildfire frequencies and sizes (Q6100557) (← links)
- Joint modeling and prediction of massive spatio-temporal wildfire count and burnt area data with the INLA-SPDE approach (Q6100559) (← links)
- Visuanimation in statistics (Q6538490) (← links)
- Full likelihood inference for max-stable data (Q6541493) (← links)
- Similarity-based clustering for patterns of extreme values (Q6548801) (← links)
- An efficient workflow for modelling high-dimensional spatial extremes (Q6581672) (← links)
- Likelihood-Free Parameter Estimation with Neural Bayes Estimators (Q6585610) (← links)
- Max-convolution processes with random shape indicator kernels (Q6596184) (← links)
- Advances in statistical modeling of spatial extremes (Q6602343) (← links)
- Spatial hierarchical modeling of threshold exceedances using rate mixtures (Q6626383) (← links)
- Practical strategies for generalized extreme value-based regression models for extremes (Q6626492) (← links)
- Partial Tail-Correlation Coefficient Applied to Extremal-Network Learning (Q6637459) (← links)
- Joint modelling of landslide counts and sizes using spatial marked point processes with sub-asymptotic mark distributions (Q6662953) (← links)
