Results 61 to 70 of about 15,041,214 (186)
Evaluating Bayesian spatial methods for modelling species distributions with clumped and restricted occurrence data. [PDF]
PLoS ONE, 2017 Statistical approaches for inferring the spatial distribution of taxa (Species Distribution Models, SDMs) commonly rely on available occurrence data, which is often clumped and geographically restricted.
David W Redding +3 more
doaj +1 more source
A Sequential Monte Carlo Method for Bayesian Poisson Process Trees
Stat, Volume 15, Issue 4, December 2026.ABSTRACT Statistical analysis of spatial point patterns often needs to deal with heterogeneous structures in intensity function estimation with possibly high‐dimensional covariate space. Likelihood based inference for spatial point process models needs to address the challenges in evaluating the multidimensional integral of random intensity function ...
Pulong Ma
wiley +1 more source
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 +2 more
openaire +2 more sources
Journal of Health, Population and Nutrition, 2021 The global prevalence of overweight (including obesity) in children under 5 years of age was 7% in 2012, and it is expected to rise to 11% by the year 2025.
Owen Paweni Loss Mtambo +1 more
doaj +1 more source
Bayesian spatial modelling of contraception effects on fertility in Mexican municipalities in 2020
Geospatial Health, 2022 The prevalence and use of contraceptive methods is an essential element to explain the behaviour of fertility and population growth. The objective of this study was to analyse the spatial correlation between the use of contraceptive methods in women of ...
Gerardo Núñez Medina
doaj +1 more source
RTMB: An R Package for Fitting Latent Variable Models With Template Model Builder
Ecology and Evolution, Volume 16, Issue 11, November 2026.Hierarchical and latent variable models are fundamental in ecology, fisheries science, and epidemiology, but fitting them efficiently relies on automatic differentiation (AD) combined with approximations such as the Laplace approximation. RTMB is an R package that exposes the full power of TMB's AD machinery directly from plain R. Users write the joint
Kasper Kristensen +4 more
wiley +1 more source
Fitting complex ecological point process models with integrated nested Laplace approximation [PDF]
, 2013 Summary 1. We highlight an emerging statistical method, integrated nested Laplace approximation (INLA), which is ideally suited for fitting complex models to many of the rich spatial data sets that ecologists wish to analyse. 2.
Gallego-Fernández, Juan B. +9 more
core +1 more source
Modeling multivariate positive‐valued time series using R‐INLA
Applied Stochastic Models in Business and IndustryAbstractIn this article, we describe fast Bayesian statistical analysis of vector positive‐valued time series, with application to interesting financial data streams. We discuss a flexible level correlated model (LCM) framework for building hierarchical models for vector positive‐valued time series.
Dutta, Chiranjit +2 more
openaire +2 more sources
Environmental ChallengesSoil 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.
Alain Matazi Kangela +8 more
doaj +1 more source
Bayesian Inference for Multivariate Spatial Models with R-INLA [PDF]
, 2023 Bayesian methods and software for spatial data analysis are generally well established now in the scientific community. Despite the wide application of spatial models, the analysis of multivariate spatial data using the integrated nested Laplace ...
Bivand, Roger S +4 more
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