Results 21 to 30 of about 7,584 (197)
Where Is the Clean Air? A Bayesian Decision Framework for Personalised Cyclist Route Selection Using R-INLA [PDF]
, 2020 Exposure to air pollution in the form of fine particulate matter (PM2.5) is known to cause diseases and cancers. Consequently, the public are increasingly seeking health warnings associated with levels of PM2.5 using mobile phone applications and ...
G Shaddick (21866612) +5 more
core +6 more sources
Spatial modelling with R-INLA: A review
, 2018 Coming up with Bayesian models for spatial data is easy, but performing inference with them can be challenging. Writing fast inference code for a complex spatial model with realistically-sized datasets from scratch is time-consuming, and if changes are ...
Bolin, David +7 more
core +5 more sources
A Fast, Flexible Simulation Framework for Bayesian Adaptive Designs-The R Package BATSS. [PDF]
Pharm StatABSTRACT The use of Bayesian adaptive designs for randomised controlled trials has been hindered by the lack of software readily available to statisticians. We have developed a new software package (Bayesian Adaptive Trials Simulator Software—BATSS) for the statistical software R, which provides a flexible structure for the fast simulation of Bayesian ...
Couturier DL +4 more
europepmc +2 more sources
Spatio-temporal disease mapping using INLA
, 2010 Spatio-temporal disease mapping models are a popular tool to describe the pattern of disease counts. They are usually formulated in a hierarchical Bayesian framework with latent Gaussian model.
Leonhard Held +3 more
core +2 more sources
Spatial field reconstruction with INLA
Astronomy & Astrophysics, 2023 Aims. Monte Carlo radiative transfer (MCRT) simulations are a powerful tool for understanding the role of dust in astrophysical systems and its influence on observations. However, due to the strong coupling of the radiation field and medium across the whole computational domain, the problem is non-local and non-linear, and such simulations are ...
Smole, Majda +3 more
openaire +2 more sources
Using INLA to fit a complex point process model with temporally varying effects – a case study [PDF]
, 2012 Integrated nested Laplace approximation (INLA) provides a fast and yet quite exact approach to fitting complex latent Gaussian models which comprise many statistical models in a Bayesian context, including log Gaussian Cox processes. This paper discusses
Soerbye, S +7 more
core +2 more sources
Multivariate spatial prediction of air pollutant concentrations with INLA [PDF]
Environmental Research Communications, 2021 Estimates of daily air pollution concentrations with complete spatial and temporal coverage are important for supporting epidemiologic studies and health impact assessments. While numerous approaches have been developed for modeling air pollution, they typically only consider each pollutant separately.
Wenlong Gong +2 more
openaire +2 more sources
Fitting complex ecological point process models with integrated nested Laplace approximation [PDF]
, 2013 Summary 1. We highlight an emerging statistical method, integrated nested Laplace approximation (INLA), which is ideally suited for fitting complex models to many of the rich spatial data sets that ecologists wish to analyse. 2.
Gallego-Fernández, Juan B. +9 more
core +1 more source
Bayesian Model Averaging with the Integrated Nested Laplace Approximation
Econometrics, 2020 The integrated nested Laplace approximation (INLA) for Bayesian inference is an efficient approach to estimate the posterior marginal distributions of the parameters and latent effects of Bayesian hierarchical models that can be expressed as latent ...
Virgilio Gómez-Rubio +2 more
doaj +1 more source
Gut Pathogens, 2019 Background Internalins are surface proteins that are utilized by Listeria monocytogenes to facilitate its invasion into human intestinal epithelial cells. The expression of a full-length InlA is one of essential virulence factors for L.
Xudong Su +9 more
doaj +1 more source