Results 1 to 10 of about 4,738 (165)

Spatial modelling of agro-ecologically significant grassland species using the INLA-SPDE approach [PDF]

Scientific Reports, 2023
The use of spatially referenced data in agricultural systems modelling has grown in recent decades, however, the use of spatial modelling techniques in agricultural science is limited.
Andrew Fichera, Rachel King, Jarrod Kath, David Cobon, Kathryn Reardon-Smith   +4 more
doaj   +7 more sources

Spatial variability and uncertainty associated with soil moisture content using INLA-SPDE combined with PyMC3 probability programming [PDF]

Scientific Reports
Spatial variability and uncertainty associated with soil volumetric moisture content (SVMC) is crucial in moisture prediction accuracy, this paper sets out to address this point of SVMC by developing data-driven model.
Yujian Yang, Xueqin Tong
exaly   +5 more sources

Using a Bayesian modelling approach (INLA-SPDE) to predict the occurrence of the Spinetail Devil Ray (Mobular mobular). [PDF]

Sci Rep, 2020
AbstractTo protect the most vulnerable marine species it is essential to have an understanding of their spatiotemporal distributions. In recent decades, Bayesian statistics have been successfully used to quantify uncertainty surrounding identified areas of interest for bycatch species.
Lezama-Ochoa N, Pennino MG, Hall MA, Lopez J, Murua H.   +4 more
europepmc   +14 more sources

Geostatistical Modelling and Web‐Based Mapping of Malaria Risks Among Children Under Five Years in Nigeria: Evidence From the 2021 Nigeria Malaria Indicator Survey [PDF]

Health Science Reports
Background Malaria is a critical public health concern in Nigeria with the country bearing an uneven burden of the disease. In Nigeria, malaria is one of the main causes of child mortality and despite all efforts to reduce malaria mortality rates, the ...
Justice Moses K. Aheto, Bakare Emmanuel Afolabi, Dolapo O. Oniyelu, Deborah O. Daniel, Steven I. Ikediashi, Oluwaseun A. Mogbojuri, Ronke D. Olorunfemi, Sodiq A. Orogun, Afeez Abidemi, Idowu I. Olasupo, Samuel A. Osikoya, Samuel A. Adeyemi, Hapiness O. Ismail, Isaac Bakare, Samson O. Olagbami, Dolapo A. Bakare, Baiyeri Samuel, Temitayo V. Irewole, Oluwafunmilayo O. Olapade, Oluwafolakemi Odunola, Oghenekevwe R. Ajewole, Joshua P. Ojo, Segun Oyedeji, Wisdom Takramah   +23 more
doaj   +3 more sources

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.
Bitaisha Nakishuka Shukuru
exaly   +4 more sources

Bayesian modelling of spatio-temporal dynamics for early-warning and control of severe malaria in Cameroon [PDF]

Parasite Epidemiology and Control
Background: Malaria is a significant public health problem in Cameroon where spatial and temporal heterogeneities in transmission make early-warning and control complicated. The traditional forecasting methods have the limitation that they are not always
Akindeh Mbuh Nji, Taiwo M. Adegoke, Sheetal P. Silal, Ali Innocent, Pascal F. Madeleine, Masso T. Sylvanie, Calvino F. Tah, Andrillene L.D. Wondeu, Christophe Antinio-Nkondjio, Jude D. Bigoga, Rose F.G. Leke, Gillian Stresman, Liwang Cui, Wilfred F. Mbacham   +13 more
doaj   +2 more sources

Data fusion in a two-stage spatio-temporal model using the INLA-SPDE approach

Spatial Statistics, 2023
This paper proposes a two-stage estimation approach for a spatial misalignment scenario that is motivated by the epidemiological problem of linking pollutant exposures and health outcomes. We use the integrated nested Laplace approximation method to estimate the parameters of a two-stage spatio-temporal model — the first stage models the exposures ...
Ben Swallow, Stephen Jun Villejo, Janine Illian   +2 more
exaly   +5 more sources

Migration-adjusted prostate cancer incidence in China: a population-based epidemiological analysis [PDF]

Frontiers in Public Health
BackgroundChina’s internal migration poses major challenges to cancer surveillance systems that rely on household-registered populations (HRP). Excluding migrants can lead to biased incidence estimates and misinformed public health planning.MethodsThis ...
Yu Zhang, Yu Zhang, Yu Zhang, Guijin Li, Guijin Li, Guijin Li, Shuxiu Hao, Shuxiu Hao, Shuxiu Hao, Huixin Sun, Huixin Sun, Huixin Sun, Huixin Sun, Linlin Du, Linlin Du, Linlin Du, Linlin Du, Xinyu Liu, Liangfang Xue, Xinshu Wang, Tong Wang, Tong Wang, Tong Wang, Qi Li   +23 more
doaj   +2 more sources

Bayesian modelling for spatially misaligned health and air pollution data through the INLA-SPDE approach

Spatial Statistics, 2019
Abstract In air pollution studies a key issue concerns the change of support: pollutant concentrations are continuous phenomena in space but their measurements are typically available at a finite number of point-referenced monitoring stations or result from numerical models.
Marta Blangiardo, Virgilio Gómez-Rubio, Michela Cameletti   +2 more
exaly   +4 more sources

The estimated incidence of uterine corpus cancers among permanent residents in mainland China using Bayesian spatial modeling [PDF]

Scientific Reports
Cancer registration in mainland China traditionally focuses on household-registered residents (HRR) and does not include the migrant population among permanent residents (PR), leading to significant selection bias.
Shuxiu Hao, Liyuan Guo, Sihong Guo, Chen Feng, Huixin Sun, Linlin Du, Guijin Li, Cheng Wang, Yu Zhang, Cunqi Lv, Qingyu Zeng, Jiacheng Li, Xinshu Wang, Tong Wang, Liping Tang, Qi Li   +15 more
doaj   +2 more sources