Results 1 to 10 of about 3,684 (165)

Spatial and temporal modeling of breast cancer mortality in Kansas: An R-INLA approach. [PDF]

PLoS ONE
IntroductionBased on Breast Cancer Statistics, 2025, breast cancer is a leading cause of death among women in the United States. Geographic disparities and associated risk factors influence breast cancer mortality over time and across spatial areas ...
Stephanie Colwell, Prabhakar Chalise, Byron Gajewski, Isuru Ratnayake, Dinesh Pal Mudaranthakam   +4 more
doaj   +3 more sources

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

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, Newell K, Lam KBH, Kurmi O, Chen Z, Kartsonaki C.   +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 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

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 Evolution
Species 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, Susan G. Jarvis, Peter A. Henrys   +2 more
doaj   +4 more sources

Computing with R-INLA: Accuracy and reproducibility with implications for the analysis of COVID-19 data

, 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

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   +5 more sources

Spatial and spatio-temporal county-level trends in COVID-19 mortality and emergency department visits in U.S. with R-INLA. [PDF]

Spat Spatiotemporal Epidemiol
Weekly 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, Panaggio MJ, Gallagher ME, Graff P, Broeker L, Weng M, Ahmad F, Sheppard M.   +7 more
europepmc   +3 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