Results 61 to 70 of about 8,734 (183)

sdmTMB: An R Package for Fast, Flexible, and User-Friendly Generalized Linear Mixed Effects Models with Spatial and Spatiotemporal Random Fields

Journal of Statistical Software
Geostatistical spatial or spatiotemporal data are common across scientific fields. However, appropriate models to analyze these data, such as generalized linear mixed effects models (GLMMs) with Gaussian Markov random fields (GMRFs), are computationally ...
Sean C. Anderson, Eric J. Ward, Philina A. English, Lewis A. K. Barnett, James T. Thorson   +4 more
doaj   +1 more source

Modeling Benthic Animals in Space and Time Using Bayesian Point Process With Cross Validation: The Case of Holoturians

Environmetrics, Volume 37, Issue 3, April 2026.
ABSTRACT Holothurian populations in the Mediterranean are relatively understudied, with limited knowledge of their spatial distribution, habitat preferences, and ecological dynamics, making their monitoring a key challenge for ecosystem assessment and sustainable management.
Daniele Poggio, Gian Mario Sangiovanni, Gianluca Mastrantonio, Giovanna Jona Lasinio, Edoardo Casoli, Stefano Moro, Daniele Ventura   +6 more
wiley   +1 more source

Bayesian spatial modelling of malaria burden in two contrasted eco-epidemiological facies in Benin (West Africa): call for localized interventions

BMC Public Health, 2022
Background Despite a global decrease in malaria burden worldwide, malaria remains a major public health concern, especially in Benin children, the most vulnerable group.
Barikissou Georgia Damien, Akoeugnigan Idelphonse Sode, Daniel Bocossa, Emmanuel Elanga-Ndille, Badirou Aguemon, Vincent Corbel, Marie-Claire Henry, Romain Lucas Glèlè Kakaï, Franck Remoué   +8 more
doaj   +1 more source

Causal Inference for Geostatistical Data Using an INLA‐based Spatial Propensity Score

Environmetrics, Volume 37, Issue 3, April 2026.
ABSTRACT In this paper, we propose a Bayesian approach for spatial causal inference based on combining spatial propensity scoring with Integrated Nested Laplace Approximation. The method models both local and spillover exposure effects via multiple likelihoods and treats counterfactuals as missing data, allowing inference also for non‐Gaussian outcomes.
Chiara Di Maria, Alessandro Albano, Mariangela Sciandra, Antonella Plaia   +3 more
wiley   +1 more source

Density estimates on a parabolic spde

, 2002
We consider a general class of parabolic spde's [formula] with (t, x) [member of] [0, T]×[0, 1] and [epsilon]Wt,x, [epsilon] > 0, a perturbed Gaussian space-time white noise. For (t, x) [member of] (0, T]×(0, 1) we prove the called Davies and Varadhan-
Márquez-Carreras, D., Mellouk, M., M. Mellouk, Márquez, David (Márquez Carreras), D. Márquez-Carreras   +4 more
core   +1 more source

Data-driven soil salinization mapping: risk prediction and uncertainty quantification based on Bayesian inference

Geoderma
Soil salinization poses a serious global threat to agricultural production and has emerged as a critical issue of land degradation. To comprehensively investigate the risks and uncertainty quantification associated with soil salinization, Yucheng County,
Yujian Yang, Ying Zhao, Rongjiang Yao, Xueqin Tong   +3 more
doaj   +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

Seroprevalence for dengue virus in a hyperendemic area and associated socioeconomic and demographic factors using a cross-sectional design and a geostatistical approach, state of São Paulo, Brazil

BMC Infectious Diseases, 2019
Background São José do Rio Preto is one of the cities of the state of São Paulo, Brazil, that is hyperendemic for dengue, with the presence of the four dengue serotypes. Objectives: to calculate dengue seroprevalence in a neighbourhood of São José do Rio
Francisco Chiaravalloti-Neto, Rafael Alves da Silva, Nathalia Zini, Gislaine Celestino Dutra da Silva, Natal Santos da Silva, Maisa Carla Pereira Parra, Margareth Regina Dibo, Cassia Fernanda Estofolete, Eliane Aparecida Fávaro, Karina Rocha Dutra, Manlio Tasso Oliveira Mota, Georgia Freitas Guimarães, Ana Carolina Bernardes Terzian, Marta Blangiardo, Mauricio Lacerda Nogueira   +14 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

Brown Bear (Ursus arctos) Field Sign Monitoring for 40 Years (1976–2015) in Northern Hokkaido, Japan, During a Wildlife Management Policy Shift

Ecological Research, Volume 41, Issue 2, March 2026.
Long‐term (1976–2015) field sign monitoring of brown bears in northern Hokkaido, Japan, yielded 2421 records (feeding signs, tracks, scats) along 9890 km of survey routes. The digitized spatiotemporal dataset provides insights into population dynamics, habitat use, and feeding behavior across a major wildlife management policy shift.
Hino Takafumi, Kanzi M. Tomita, Hiroto Takinami, Taiki Ito, Muku Tsujino, Kazuaki Ikeda, Yu Endo, Shiho Furumaki, Takuya Ono, Nobuo Ishiyama   +9 more
wiley   +1 more source