Estimating ambient air pollutant levels in Suzhou through the SPDE approach with R-INLA.
Int J Hyg Environ Health, 2021 Spatio-temporal models of ambient air pollution can be used to predict pollutant levels across a geographical region. These predictions may then be used as estimates of exposure for individuals in analyses of the health effects of air pollution. Integrated nested Laplace approximations is a method for Bayesian inference, and a fast alternative to ...
Wright N +5 more
europepmc +4 more sources
Multilevel Bivariate Areal Modelling for School Data: An Application with R-INLA
This paper studies the relationship between the territorial endowment of school infrastructure and services in Italy and the performance of high school students, expressed by the Invalsi scores for the second year of high school, by means of spatial ...
Leonardo Cefalo, Virgilio Gómez-Rubio
openaire +2 more sources
Seabird Prey in Space and Time: Combining Multiple Datasets to Model the Distribution of Sandeel (<i>Ammodytes marinus</i>) and Sprat (<i>Sprattus sprattus</i>) in the North Sea. [PDF]
Ecol EvolForage fish are key prey and commercial species in the North Sea ecosystem, but estimates of their biomass over detailed spatial and temporal scales is currently limited. To fill this vital research gap we employ Hierarchical Bayesian spatiotemporal models of sandeel (Ammodytes marinus) and sprat (Sprattus sprattus) in the North Sea, providing fine ...
Benaksas S +5 more
europepmc +2 more sources
Molecular Characterisation and Antimicrobial Resistance Patterns of Listeria monocytogenes From Dairy Sources. [PDF]
Vet Med SciThis study presents a comprehensive surveillance of L. monocytogenes along the dairy supply chain, from raw milk collection to final products and environmental sources. The methodological framework encompasses conventional microbiological isolation and identification, followed by phenotypic antimicrobial susceptibility testing and calculation of the ...
Heidari MR +3 more
europepmc +2 more sources
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 +5 more sources
Competing risks joint models using R-INLA [PDF]
Statistical Modelling, 2020 The methodological advancements made in the field of joint models are numerous. None the less, the case of competing risks joint models has largely been neglected, especially from a practitioner's point of view. In the relevant works on competing risks joint models, the assumptions of a Gaussian linear longitudinal series and proportional cause ...
Van Niekerk, Janet +2 more
openaire +3 more sources
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
Spatial and spatio-temporal county-level trends in COVID-19 mortality and emergency department visits in U.S. with R-INLA. [PDF]
Spat Spatiotemporal EpidemiolWeekly county-level COVID-19 mortality and emergency department (ED) visits data are critical data sources for understanding COVID-19 trends, but subject to reporting delays, sampling variability, potential instability and concerns due to statistical reliability as well as data suppression due to small numbers and the need to protect personally ...
Khan D +7 more
europepmc +3 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 +3 more
core +2 more sources
Where Is the Clean Air? A Bayesian Decision Framework for Personalised Cyclist Route Selection Using R-INLA [PDF]
Bayesian Analysis, 2021 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dawkins, LC +5 more
openaire +4 more sources