High-resolution Bayesian mapping of landslide hazard with unobserved trigger event
From MaRDI portal
Publication:2170422
DOI10.1214/21-AOAS1561zbMath1498.62289arXiv2006.07902MaRDI QIDQ2170422
Thomas Opitz, Haakon Bakka, Raphaël Huser, Luigi Lombardo
Publication date: 5 September 2022
Published in: The Annals of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2006.07902
integrated nested Laplace approximation (INLA)model complexitylandslidelog-Gaussian Cox processspace-varying regressiontriggering event
Inference from spatial processes (62M30) Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15)
Related Items
Cites Work
- Unnamed Item
- Understanding predictive information criteria for Bayesian models
- Space-varying regression models: specifications and simulation
- Bayesian inference and model assessment for spatial point patterns using posterior predictive samples
- Penalising model component complexity: a principled, practical approach to constructing priors
- INLA goes extreme: Bayesian tail regression for the estimation of high spatio-temporal quantiles
- A toolbox for fitting complex spatial point process models using integrated nested Laplace approximation (INLA)
- Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
- Accurate Approximations for Posterior Moments and Marginal Densities
- Log Gaussian Cox Processes
- Spatial Modeling With Spatially Varying Coefficient Processes
- Gaussian Markov Random Fields
- Bayesian computation for Log-Gaussian Cox processes: a comparative analysis of methods
- Definitions, methods, and applications in interpretable machine learning
- Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA
This page was built for publication: High-resolution Bayesian mapping of landslide hazard with unobserved trigger event
