Results 91 to 100 of about 5,509 (173)
: This paper formulates and compares a general class of spatiotemporal models for uni-variate space-time geostatistical data. The implementation of stochastic partial differential equation (SPDE) approach combined with integrated nested Laplace ...
Faes, Christel +5 more
core +1 more source
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
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 +2 more
core +1 more source
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 +18 more
doaj +1 more source
Bayesian Optimization (BO) is a popular method for efficiently optimizing expensive black-box objectives. However, BO utilizing standard Gaussian Processes is ill-suited for doubly stochastic Cox Processes that are often used in spatio-temporal problem spaces.
Yang, Kaichuang +2 more
openaire +2 more sources
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population estimates have been developed to fill data gaps in resource-poor countries where census data are either outdated or incomplete.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 +6 more
openaire +1 more source
Comparing Global and Local Specification of Spatially Varying Anisotropy
I denne oppgaven tar vi for oss to tilnærminger til ikke-stasjonær romlig modellering med gaussiske stokastiske felt (GRF-er), og sammenligner disse. Den første tilnærmingen tar i bruk en stokastisk partiell differensialligning (SPDE), som har en GRF som
Isaksen, Mathias Leander
core
Species distribution models (SDMs) are widely used to standardize spatially unbalanced data, project climate impacts and identify habitat for conservation.
Max Lindmark +2 more
doaj +1 more source
Spatio-temporal models Valley fever incidence using INLA and stochastic PDE\u27s
honors thesisCollege of SciencePhysics & AstronomyKatharine WalterValley fever, caused by the Coccidioides fungus is a disease of increasing concern in the American West.
Sussman, Jacob
core
The impact of choosing different meshes under INLA/SPDE framework for geostatistical modelling [PDF]
openaire +1 more source

