Results 151 to 160 of about 7,865 (191)

Rapid global growth and intensification of dengue since 1990

Brady O, Lim A, Joshi K, Lakshminarayanan P, Susong K, Clarke J, Poongavanan J, Quandelacy T, Cousin E, Tegally H, LIM JT, Mosser J, Johansson M, Hay S.   +13 more
europepmc   +1 more source

A New Avenue for Bayesian Inference With INLA

Computational Statistics and Data Analysis, 2023
Integrated Nested Laplace Approximations (INLA) has been a successful approximate Bayesian inference framework since its proposal by Rue et al. (2009). The increased computational efficiency and accuracy when compared with sampling-based methods for Bayesian inference like MCMC methods, are some contributors to its success. Ongoing research in the INLA
Denis Rustand, Håvard Rue, Janet van Niekerk   +2 more
exaly   +6 more sources

Bayesian Computing With INLA: New Features [PDF]

Computational Statistics and Data Analysis, 2013
The INLA approach for approximate Bayesian inference for latent Gaussian models has been shown to give fast and accurate estimates of posterior marginals and also to be a valuable tool in practice via the R-package R-INLA. In this paper we formalize new developments in the R-INLA package and show how these features greatly extend the scope of models ...
Håvard Rue, Finn Lindgren, Daniel Simpson   +2 more
exaly   +7 more sources

Bayesian Survival Analysis With INLA

Statistics in Medicine
This tutorial shows how various Bayesian survival models can be fitted using the integrated nested Laplace approximation in a clear, legible, and comprehensible manner using the INLA and INLAjoint R‐packages. Such models include accelerated failure time, proportional hazards, mixture cure, competing risks, multi‐state, frailty, and joint models of ...
Denis Rustand, Håvard Rue, Janet van Niekerk   +2 more
exaly   +6 more sources

INLA ⁺ : Approximate Bayesian Inference for Non-Sparse Models Using HPC

Statistics and Computing
The integrated nested Laplace approximations (INLA) method has become a widely utilized tool for researchers and practitioners seeking to perform approximate Bayesian inference across various fields of application.
Håvard Rue, Janet van Niekerk, Esmail Abdul Fattah   +2 more
exaly   +2 more sources

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Case studies in Bayesian computation using INLA

2010
Latent Gaussian models are a common construct in statistical applications where a latent Gaussian field, indirectly observed through data, is used to model, for instance, time and space dependence or the smooth effect of covariates. Many well-known statistical models, such as smoothing-spline models, space time models, semiparametric regression ...
Sara Martino, Håvard Rue
openaire   +1 more source

A Review of INLA

2022
Nalini Ravishanker, Balaji Raman, Refik Soyer   +2 more
openaire   +1 more source