Results 1 to 10 of about 3,465 (151)

Spatio-temporal pattern and risk factors of HIV/AIDS prevalence in Zhejiang, China, from 2005 to 2022 using R-INLA [PDF]

One Health
Background: 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, Yifan Chen, Jinglei Zheng, Wei Cheng, Yurong Jing, Yushu Zhang, Chengliang Chai, Chengxiu Ling, Ying Wang   +8 more
doaj   +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 Methodology
Background 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, Najmeh Nakhaei Rad, Ding-Geng Chen   +2 more
doaj   +2 more sources

Generating geochemical and mineralogy distributions of soil in the conterminous United States using Bayesian hierarchical spatial models [PDF]

MethodsX
Characterizing geochemical and mineralogical soil distributions across large spatial extents is essential for understanding mineral resources, ecosystem processes, and environmental risks.
Kristin J. Bondo, Tiffany M. Wolf, W. David Walter   +2 more
doaj   +2 more sources

JSTMapp: A web-based joint spatiotemporal modelling and mapping application for epidemiologists. [PDF]

PLoS ONE
Disease mapping models help create disease risk maps, which public health policymakers can use to design disease control and monitoring programmes.
Alfred Ngwira, Samuel O M Manda, Esron D Karimuribo, Sharadhuli I Kimera   +3 more
doaj   +2 more sources

Predicting spatio-temporal dynamics of dengue using INLA (integrated nested laplace approximation) in Yogyakarta, Indonesia [PDF]

BMC Public Health
Introduction 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, Tri Baskoro Tunggul Satoto, Danardono   +2 more
doaj   +2 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, Roger S. Bivand, Håvard Rue   +2 more
doaj   +1 more source

New Frontiers in Bayesian Modeling Using the INLA Package in R

Journal of Statistical Software, 2021
The INLA package provides a tool for computationally efficient Bayesian modeling and inference for various widely used models, more formally the class of latent Gaussian models.
Janet Van Niekerk, Haakon Bakka, Håvard Rue, Olaf Schenk   +3 more
doaj   +1 more source

Laplace approximation for conditional autoregressive models for spatial data of diseases

MethodsX, 2022
Conditional autoregressive (CAR) distributions are used to account for spatial autocorrelation in small areal or lattice data to assess the spatial risks of diseases.
Guiming Wang
doaj   +1 more source

Estimating Animal Abundance with N-Mixture Models Using the R-INLA Package for R

Journal of Statistical Software, 2020
Successful management of wildlife populations requires accurate estimates of abundance. Abundance estimates can be confounded by imperfect detection during wildlife surveys.
Timothy D. Meehan, Nicole L. Michel, Håvard Rue   +2 more
doaj   +1 more source

Bayesian Multivariate Spatial Models for Lattice Data with INLA

Journal of Statistical Software, 2021
The INLAMSM package for the R programming language provides a collection of multivariate spatial models for lattice data that can be used with the INLA package for Bayesian inference.
Francisco Palmí-Perales, Virgilio Gómez-Rubio, Miguel A. Martinez-Beneito   +2 more
doaj   +1 more source