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04/26/2023
High stakes classification with multiple unknown classes based on imperfect data
High stakes classification refers to classification problems where erron...
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06/14/2020
High-resolution Bayesian mapping of landslide hazard with unobserved trigger event
Statistical models for landslide hazard enable mapping of risk factors a...
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06/08/2020
The diffusion-based extension of the Matérn field to space-time
The Matérn field is the most well known family of covariance functions u...
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02/16/2020
A principled distance-based prior for the shape of the Weibull model
The use of flat or weakly informative priors is popular due to the objec...
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09/04/2019
Competing risks joint models using R-INLA
The methodological advancements made in the field of joint models are nu...
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07/27/2019
Max-and-Smooth: a two-step approach for approximate Bayesian inference in latent Gaussian models
With modern high-dimensional data, complex statistical models are necess...
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07/24/2019
New frontiers in Bayesian modeling using the INLA package in R
The INLA package provides a tool for computationally efficient Bayesian ...
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07/10/2019
Approximate Bayesian inference for spatial flood frequency analysis
Extreme floods cause casualties, widespread property damage, and damage ...
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01/27/2019
Joint models as latent Gaussian models - not reinventing the wheel
Joint models have received increasing attention during recent years with...
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07/23/2018
Geostatistical modeling to capture seismic-shaking patterns from earthquake-induced landslides
In this paper, we investigate earthquake-induced landslides using a geos...
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03/10/2018
How to solve the stochastic partial differential equation that gives a Matérn random field using the finite element method
This tutorial teaches parts of the finite element method (FEM), and solv...
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02/18/2018
Spatial modelling with R-INLA: A review
Coming up with Bayesian models for spatial data is easy, but performing ...
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02/04/2018