Spatio-temporal pattern and risk factors of HIV/AIDS prevalence in Zhejiang, China, from 2005 to 2022 using R-INLA [PDF]
One HealthBackground: The number of reported HIV/AIDS cases in the Zhejiang province, China, has increased drastically. However, spatial disparity and temporal trends in HIV/AIDS risk at the fine level remain unclear.
Yifan Tang +8 more
doaj +4 more sources
Estimating Spatial Econometrics Models with Integrated Nested Laplace Approximation
Mathematics, 2021 The integrated nested Laplace approximation (INLA) provides a fast and effective method for marginal inference in Bayesian hierarchical models. This methodology has been implemented in the R-INLA package which permits INLA to be used from within R ...
Virgilio Gómez-Rubio +2 more
doaj +3 more sources
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
Computationally efficient Bayesian inference for semi-parametric joint models of competing risks survival and skewed longitudinal data using integrated nested Laplace approximation [PDF]
BMC Medical Research MethodologyBackground Joint modeling is widely used in medical research to properly analyze longitudinal biomarkers and survival outcomes simultaneously and to guide appropriate interventions in public health.
Melkamu Molla Ferede +2 more
doaj +2 more sources
Bayesian Spatial Modelling with R-INLA [PDF]
Journal of Statistical Software, 2015 The principles behind the interface to continuous domain spatial models in the R- INLA software package for R are described. The integrated nested Laplace approximation (INLA) approach proposed by Rue, Martino, and Chopin (2009) is a computationally ...
Finn Lindgren, Håvard Rue
doaj +4 more sources
Spatio‐temporal data integration for species distribution modelling in R‐INLA
Methods in Ecology and EvolutionSpecies distribution modelling is a highly used tool for understanding and predicting biodiversity change, and recent work has emphasised the importance of understanding how species distributions change over both time and space.
Fiona M. Seaton +2 more
doaj +4 more sources
JSTMapp: A web-based joint spatiotemporal modelling and mapping application for epidemiologists. [PDF]
PLoS ONEDisease mapping models help create disease risk maps, which public health policymakers can use to design disease control and monitoring programmes.
Alfred Ngwira +3 more
doaj +2 more sources
, 2021 The statistical methods used to analyze medical data are becoming increasingly complex. Novel statistical methods increasingly rely on simulation studies to assess their validity. Such assessments typically appear in statistical or computational journals, and the methodology is later introduced to the medical community through tutorials.
Khan K, Luo H, Xi W.
europepmc +3 more sources
Addressing spatial confounding in geostatistical regression models: An R‐INLA approach
Methods in Ecology and EvolutionSpatial confounding, which has been studied extensively in recent years, can explain inconsistencies between results obtained by regression models with and without spatial modelling.
Jérémy Lamouroux +4 more
doaj +4 more sources
Predicting spatio-temporal dynamics of dengue using INLA (integrated nested laplace approximation) in Yogyakarta, Indonesia [PDF]
BMC Public HealthIntroduction Dengue is a mosquito-borne disease caused by the dengue virus, primarily transmitted by Aedes aegypti and Aedes albopictus. Its incidence fluctuates due to spatial and temporal factors, necessitating robust modeling approaches for prediction
Marko Ferdian Salim +2 more
doaj +2 more sources