Results 91 to 100 of about 4,738 (165)

Correction to: A Bayesian Model for Estimating the Effects of Human Disturbance on Wildlife Habitats Based on Nighttime Light Data and INLA‑SPDE [PDF]

Applied Spatial Analysis and Policy, 2022
Changbai Xi, Zhaoning Wu, Tianlu Qian, Lu Liu, Jiechen Wang   +4 more
openaire   +1 more source

High-Resolution Spatiotemporal Forecasting with Missing Observations Including an Application to Daily Particulate Matter 2.5 Concentrations in Jakarta Province, Indonesia

Mathematics
Accurate forecasting of high-resolution particulate matter 2.5 (PM2.5) levels is essential for the development of public health policy. However, datasets used for this purpose often contain missing observations.
I Gede Nyoman Mindra Jaya, Henk Folmer
doaj   +1 more source

The SPDE approach in spatio-temporal Bayesian models for atmospheric pollution monitoring ​

reservedQuesta tesi esplora l'applicazione dei metodi bayesiani tramite l’utilizzo dell’Integrated Nested Laplace Approximation (INLA) nell'analisi dei dati spazio-temporali, concentrandosi in particolare sui dati geostatistici e sul monitoraggio dell ...
MONTE, VALENTINA
core  

Spatial modelling with R-INLA: A review

, 2018
Coming up with Bayesian models for spatial data is easy, but performing inference with them can be challenging. Writing fast inference code for a complex spatial model with realistically-sized datasets from scratch is time-consuming, and if changes are ...
Bolin, David, Bakka, Haakon, Riebler, Andrea, Simpson, Daniel, Lindgren, Finn, Rue, Haavard, Krainski, Elias, Fuglstad, Geir-Arne   +7 more
core  

Geospatial analysis of immunisation outcomes in Nigeria using a Bayesian geostatistical approach and an interactive dashboard

Discover Public Health
Background Nigeria’s significant contribution to the global pool of zero-dose children persists despite ongoing immunisation investments. This coverage deficits in Kano and Lagos states serve as stark indicators of underlying structural and socio ...
Chijioke Kaduru, Idim Godwin, Olamide Akeboi, Karinate Cyril-Egware, Sharon Uzoma, Maduekwe Vivian, Ebuka Nwafia, Oshodi Esther, Tijjani Habib, Shehu Abdullahi, Rehanat Amusu, Jedydah Atieno, Koko Aadum, Ojonimi Alfred, Geraldine Mbagwu, Ganiyat Eshikhena, Ugomma Nyananyo, Josephina Obande, Ezra Gayawan   +18 more
doaj   +1 more source

Efficient Bayesian Hierarchical Small Area Population Estimation Using INLA-SPDE: Integrating Multiple Data Sources and Spatial-Autocorrelation

Statistical modelling approaches which produce fine spatial resolution population estimates have been developed to fill data gaps in resource-poor countries where census data are either outdated or incomplete. These population modelling methods often draw upon recent georeferenced sample population enumeration datasets to predict population density and
Chibuzor Christopher Nnanatu, Ortis Yankey, Anaclet D. Dzossa, Thomas Abbott, Assane Gadiaga, Attila Lazar, Andrew Tatem   +6 more
openaire   +1 more source

Estimating scale‐dependent covariate responses using two‐dimensional diffusion derived from the stochastic partial differential equation method

Methods in Ecology and Evolution
Species distribution models (SDMs) are widely used to standardize spatially unbalanced data, project climate impacts and identify habitat for conservation.
Max Lindmark, Sean C. Anderson, James T. Thorson   +2 more
doaj   +1 more source

Spatial data fusion adjusting for preferential sampling using INLA and SPDE [PDF]

Spatially misaligned data can be fused by using a Bayesian melding model that assumes that underlying all observations there is a spatially continuous Gaussian random field process.
Moraga, Paula, Zhong, Ruiman, Amaral, André Victor Ribeiro   +2 more
core   +1 more source

The impact of choosing different meshes under INLA/SPDE framework for geostatistical modelling [PDF]

, 2018
openaire   +1 more source

Finite Difference Approximation for Linear Stochastic Partial Differential Equations with Method of Lines [PDF]

A stochastic partial differential equation, or SPDE, describes the dynamics of a stochastic process defined on a space-time continuum. This paper provides a new method for solving SPDEs based on the method of lines (MOL).
McDonald, Stuart
core