Results 51 to 60 of about 3,465 (151)

Graphical outputs and Spatial Cross-validation for the R-INLA package using INLAutils

, 2020
Statistical analyses proceed by an iterative process of model fitting and checking. The R-INLA package facilitates this iteration by fitting many Bayesian models much faster than alternative MCMC approaches. As the interpretation of results and model objects from Bayesian analyses can be complex, the R package INLAutils provides users with easily ...
Lucas, Tim, Python, Andre, Redding, David   +2 more
openaire   +2 more sources

Spatiotemporal Patterns and Socioeconomic Determinants of Pulmonary Tuberculosis in Piauí, Northeast Brazil, 2001–2024

Tropical Medicine &International Health, EarlyView.
ABSTRACT Background Pulmonary tuberculosis (PTB) remains a major public health problem, strongly associated with social and territorial inequalities. This study aimed to analyse temporal trends, spatiotemporal transmission patterns and socioeconomic determinants of PTB in the state of Piauí, Northeast Brazil, from 2001 to 2024.
José Mário Nunes da Silva, Viriato Campelo, Walter Massa Ramalho   +2 more
wiley   +1 more source

Coarse‐to‐Fine Spatial Modeling: A Scalable, Machine‐Learning‐Compatible Framework

Geographical Analysis, Volume 58, Issue 2, April 2026.
ABSTRACT This study proposes coarse‐to‐fine spatial modeling (CFSM) as a scalable and machine learning‐compatible alternative to conventional spatial process models. Unlike conventional covariance‐based spatial models, CFSM represents spatial processes using a multiscale ensemble of local models.
Daisuke Murakami, Alexis Comber, Takahiro Yoshida, Narumasa Tsutsumida, Chris Brunsdon, Tomoki Nakaya   +5 more
wiley   +1 more source

Beyond Local Footprints: Disentangling Large‐Scale Redistribution and Local Abundance Responses to Offshore Wind Farms

Ecology and Evolution, Volume 16, Issue 3, March 2026.
We combine regression‐based species distribution models with a mechanistic redistribution component to assess how regional human activities affect animal distribution and abundance across spatial scales. Applied to common murres (Uria aalge) in the German North Sea, the framework indicates scenario‐based reductions in numbers within German waters of 18.
Moritz Mercker, Verena Peschko, Kai Borkenhagen, Nele Markones, Henriette Schwemmer, Volker Dierschke, Stefan Garthe   +6 more
wiley   +1 more source

Identifying the climatic drivers of honey bee disease in England and Wales

Scientific Reports, 2021
Honey bee colony health has received considerable attention in recent years, with many studies highlighting multifactorial issues contributing to colony losses.
Ben W. Rowland, Stephen P. Rushton, Mark D. F. Shirley, Mike A. Brown, Giles E. Budge   +4 more
doaj   +1 more source

Skewed Probit Regression

Revstat Statistical Journal, 2021
Skewed probit regression is but one example of a statistical model that generalizes a simpler model, like probit regression. All skew-symmetric distributions and link functions arise from symmetric distributions by incorporating a skewness parameter ...
Janet van Niekerk , Håvard Rue
doaj   +1 more source

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

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

Species distribution modeling with expert elicitation and Bayesian calibration

Ecography, Volume 2026, Issue 3, March 2026.
Species distribution models (SDM) are key tools in ecology, conservation, and natural resources management. They are traditionally trained with data on direct species observations. However, if collecting species data is difficult or expensive, complementary information sources on species distributions are needed.
Karel Kaurila, Sanna Kuningas, Antti Lappalainen, Jarno Vanhatalo   +3 more
wiley   +1 more source