research
∙
08/26/2023
A flexible Bayesian tool for CoDa mixed models: logistic-normal distribution with Dirichlet covariance
Compositional Data Analysis (CoDa) has gained popularity in recent years...
share
research
∙
03/27/2023
Towards black-box parameter estimation
Deep learning algorithms have recently shown to be a successful tool in ...
research
∙
10/10/2022
Leave-group-out cross-validation for latent Gaussian models
Evaluating predictive performance is essential after fitting a model and...
research
∙
06/18/2022
Approximate Bayesian Inference for the Interaction Types 1, 2, 3 and 4 with Application in Disease Mapping
We address in this paper a new approach for fitting spatiotemporal model...
research
∙
04/14/2022
A new avenue for Bayesian inference with INLA
Integrated Nested Laplace Approximations (INLA) has been a successful ap...
research
∙
12/06/2021
Joint Posterior Inference for Latent Gaussian Models with R-INLA
Efficient Bayesian inference remains a computational challenge in hierar...
research
∙
11/25/2021
Correcting the Laplace Method with Variational Bayes
Approximate inference methods like the Laplace method, Laplace approxima...
research
∙
06/14/2021
Smart Gradient – An Adaptive Technique for Improving Gradient Estimation
Computing the gradient of a function provides fundamental information ab...
research
∙
10/26/2020
Bayesian Estimation of Two-Part Joint Models for a Longitudinal Semicontinuous Biomarker and a Terminal Event with R-INLA: Interests for Cancer Clinical Trial Evaluation
Two-part joint model for a longitudinal semicontinuous biomarker and a t...
research
∙
09/20/2020
Skewed probit regression – Identifiability, contraction and reformulation
Skewed probit regression is but one example of a statistical model that ...
research
∙
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...
research
∙
11/22/2019
A Novel Method of Marginalisation using Low Discrepancy Sequences for Integrated Nested Laplace Approximations
Recently, it has been shown that approximations to marginal posterior di...
research
∙
09/04/2019
Competing risks joint models using R-INLA
The methodological advancements made in the field of joint models are nu...
research
∙
07/24/2019
New frontiers in Bayesian modeling using the INLA package in R
The INLA package provides a tool for computationally efficient Bayesian ...
research
∙
07/16/2019
Improving Bayesian Local Spatial Models in Large Data Sets
Environmental processes resolved at a sufficiently small scale in space ...
research
∙
01/27/2019
Joint models as latent Gaussian models - not reinventing the wheel
Joint models have received increasing attention during recent years with...
research
∙
04/10/2018
