Compositional Data Analysis (CoDa) has gained popularity in recent years...
Deep learning algorithms have recently shown to be a successful tool in
...
Evaluating predictive performance is essential after fitting a model and...
We address in this paper a new approach for fitting spatiotemporal model...
Integrated Nested Laplace Approximations (INLA) has been a successful
ap...
Efficient Bayesian inference remains a computational challenge in
hierar...
Approximate inference methods like the Laplace method, Laplace approxima...
Computing the gradient of a function provides fundamental information ab...
Two-part joint model for a longitudinal semicontinuous biomarker and a
t...
Skewed probit regression is but one example of a statistical model that
...
The use of flat or weakly informative priors is popular due to the objec...
Recently, it has been shown that approximations to marginal posterior
di...
The methodological advancements made in the field of joint models are
nu...
The INLA package provides a tool for computationally efficient Bayesian
...
Environmental processes resolved at a sufficiently small scale in space ...
Joint models have received increasing attention during recent years with...
Quantile regression is a class of methods voted to the modelling of
cond...