Results 71 to 80 of about 5,528 (174)

geoCount: An R Package for the Analysis of Geostatistical Count Data

Journal of Statistical Software, 2015
We describe the R package geoCount for the analysis of geostatistical count data. The package performs Bayesian analysis for the Poisson-lognormal and binomial-logitnormal spatial models, which are subclasses of the class of generalized linear spatial ...
Liang Jing, Victor De Oliveira
doaj   +1 more source

Fine-Tuning Heat Stress Algorithms to Optimise Global Predictions of Mass Coral Bleaching

Remote Sensing, 2021
Increasingly intense marine heatwaves threaten the persistence of many marine ecosystems. Heat stress-mediated episodes of mass coral bleaching have led to catastrophic coral mortality globally.
Liam Lachs, John C Bythell, Holly K East, Alasdair J Edwards, Peter J Mumby, William J Skirving, Blake L Spady, James R. Guest   +7 more
doaj   +1 more source

Fast calibrated additive quantile regression

, 2020
We propose a novel framework for fitting additive quantile regression models, which provides well calibrated inference about the conditional quantiles and fast automatic estimation of the smoothing parameters, for model structures as diverse as those ...
Azzalini A., Brent R. P., Hastie T., Hothorn T., Jones M., Margaux Zaffran, Matteo Fasiolo, Raphaël Nedellec, Robert C., Simon N. Wood, Yannig Goude, Yee T. W.   +11 more
core   +1 more source

Bayesian Inference for Spatially‐Temporally Misaligned Data Using Predictive Stacking

Environmetrics, Volume 37, Issue 2, March 2026.
ABSTRACT Air pollution remains a major environmental risk factor that is often associated with adverse health outcomes. However, quantifying and evaluating its effects on human health is challenging due to the complex nature of exposure data. Recent technological advances have led to the collection of various indicators of air pollution at increasingly
Soumyakanti Pan, Sudipto Banerjee
wiley   +1 more source

Geospatial analysis, web-based mapping and determinants of prostate cancer incidence in Georgia counties: evidence from the 2012–2016 SEER data

BMC Cancer, 2021
Background Prostate cancer (CaP) cases are high in the United States. According to the American Cancer Society, there are an estimated number of 174,650 CaP new cases in 2019.
Justice Moses K. Aheto, Ovie A. Utuama, Getachew A. Dagne   +2 more
doaj   +1 more source

Coherent Disaggregation and Uncertainty Quantification for Spatially Misaligned Data

Environmetrics, Volume 37, Issue 2, March 2026.
ABSTRACT Spatial misalignment arises when datasets are aggregated or collected at different spatial scales, leading to information loss. We develop a Bayesian disaggregation framework that links misaligned data to a continuous‐domain model through an iteratively linearised integration scheme implemented with the Integrated Nested Laplace Approximation (
Man Ho Suen, Mark Naylor, Finn Lindgren
wiley   +1 more source

Bayesian spatial prediction of soil organic carbon stocks in eastern DRC using INLA-SPDE and environmental covariates

Environmental Challenges
Soil organic carbon (SOC) plays a critical role in climate mitigation and agricultural sustainability, yet its spatial distribution in the eastern Democratic Republic of the Congo (DRC) remains poorly quantified.
Alain Matazi Kangela, Bitaisha Nakishuka Shukuru, Serge Mugisho Mukotanyi, Gerard Imani, Yannick Mugumaarhama, Daniel Muhindo Iragi, Dieudonné Shamamba Bahati, Janvier Bigabwa Bashagaluke, Wivine Munyahali   +8 more
doaj   +1 more source

Spatiotemporal modeling of ecological and sociological predictors of West Nile virus in Suffolk County, NY, mosquitoes

Ecosphere, 2017
Suffolk County, New York, is a locus for West Nile virus (WNV) infection in the American northeast that includes the majority of Long Island to the east of New York City.
Mark H. Myer, Scott R. Campbell, John M. Johnston   +2 more
doaj   +1 more source

An Extended Simplified Laplace strategy for Approximate Bayesian inference of Latent Gaussian Models using R-INLA

, 2022
Various computational challenges arise when applying Bayesian inference approaches to complex hierarchical models. Sampling-based inference methods, such as Markov Chain Monte Carlo strategies, are renowned for providing accurate results but with high computational costs and slow or questionable convergence.
Chiuchiolo, Cristian, van Niekerk, Janet, Rue, Håvard   +2 more
openaire   +2 more sources

A standardization procedure to incorporate variance partitioning‐based priors in latent Gaussian models

Scandinavian Journal of Statistics, Volume 53, Issue 1, Page 364-394, March 2026.
ABSTRACT Latent Gaussian models (LGMs) are a subset of Bayesian Hierarchical models where Gaussian priors, conditional on variance parameters, are assigned to all effects in the model. LGMs are employed in many fields for their flexibility and computational efficiency. However, practitioners find prior elicitation on the variance parameters challenging
Luisa Ferrari, Massimo Ventrucci
wiley   +1 more source