Results 11 to 20 of about 20,297 (180)
Spatio‐temporal occupancy models with INLA
Methods in Ecology and EvolutionModern methods for quantifying, predicting and mapping species distributions have played a crucial part in biodiversity conservation. Occupancy models have become a popular choice for analysing species occurrence data due to their ability to separate out
Jafet Belmont +3 more
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Bayesian Spatial Modelling with R-INLA [PDF]
Journal of Statistical Software, 2015 The principles behind the interface to continuous domain spatial models in the R- INLA software package for R are described. The integrated nested Laplace approximation (INLA) approach proposed by Rue, Martino, and Chopin (2009) is a computationally ...
Finn Lindgren, Håvard Rue
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Spatial modeling with R‐INLA: A review [PDF]
WIREs Computational Statistics, 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 made to the model, there is little guarantee that the code performs well.
Bakka, Haakon +8 more
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Spatial field reconstruction with INLA
Astronomy & Astrophysics, 2023 Aims. Monte Carlo radiative transfer (MCRT) simulations are a powerful tool for understanding the role of dust in astrophysical systems and its influence on observations. However, due to the strong coupling of the radiation field and medium across the whole computational domain, the problem is non-local and non-linear, and such simulations are ...
Smole, Majda +3 more
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Bayesian Inference for Multivariate Spatial Models with INLA
The R Journal, 2023 Bayesian methods and software for spatial data analysis are generally now well established in the scientific community. Despite the wide application of spatial models, the analysis of multivariate spatial data using R-INLA has not been widely described in the existing literature.
Palmí-Perales, Francisco +4 more
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A Bayesian spatio-temporal model of panel design data: airborne particle number concentration in Brisbane, Australia [PDF]
, 2013 This paper outlines a methodology for semi-parametric spatio-temporal modelling of data which is dense in time but sparse in space, obtained from a split panel design, the most feasible approach to covering space and time with limited equipment. The data
Box G. E. P. +6 more
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Spatial and spatio-temporal models with R-INLA [PDF]
Spatial and Spatio-temporal Epidemiology, 2013 During the last three decades, Bayesian methods have developed greatly in the field of epidemiology. Their main challenge focusses around computation, but the advent of Markov Chain Monte Carlo methods (MCMC) and in particular of the WinBUGS software has opened the doors of Bayesian modelling to the wide research community. However model complexity and
Blangiardo, Marta +3 more
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Spatial Data Analysis with R-INLA with Some Extensions
Journal of Statistical Software, 2015 The integrated nested Laplace approximation (INLA) provides an interesting way of approximating the posterior marginals of a wide range of Bayesian hierarchical models.
Roger Bivand +2 more
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Bayesian Model Averaging with the Integrated Nested Laplace Approximation
Econometrics, 2020 The integrated nested Laplace approximation (INLA) for Bayesian inference is an efficient approach to estimate the posterior marginal distributions of the parameters and latent effects of Bayesian hierarchical models that can be expressed as latent ...
Virgilio Gómez-Rubio +2 more
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Gut Pathogens, 2019 Background Internalins are surface proteins that are utilized by Listeria monocytogenes to facilitate its invasion into human intestinal epithelial cells. The expression of a full-length InlA is one of essential virulence factors for L.
Xudong Su +9 more
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