Results 21 to 30 of about 6,671 (202)

Spatial modelling with R-INLA: A review [PDF]

, 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, Rue, Håvard, Fuglstad, Geir-Arne, Riebler, Andrea, Bolin, David, Krainski, Elias, Simpson, Daniel, Lindgren, Finn   +7 more
openaire   +3 more sources

Multivariate spatial prediction of air pollutant concentrations with INLA [PDF]

Environmental Research Communications, 2021
Estimates of daily air pollution concentrations with complete spatial and temporal coverage are important for supporting epidemiologic studies and health impact assessments. While numerous approaches have been developed for modeling air pollution, they typically only consider each pollutant separately.
Wenlong Gong, Brian J Reich, Howard H Chang   +2 more
openaire   +2 more sources

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, Rino-Silvestre, João, González-Gaitán, Santiago, Stalevski, Marko   +3 more
openaire   +2 more sources

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., Travis, Justin M. J., Illian, Janine Baerbel, Esquivias, M. Paz, Martino, Sara, Zunzunegui, Maria, Illian, Janine B., Warton, David, Sørbye, Sigrunn H., Travis, Justin M.   +9 more
core   +1 more source

Respective ability of InlA and InlA^m to promote bacterial entry into hEcad- and mEcad-expressing cells. [PDF]

, 2013
Bacterial entry into hEcad-expressing human epithelial cells (LoVo) (A for Lm and B for Li) and mEcad-expressing mouse epithelial cells (Nme) (C for Lm and D for Li) was performed by counting intracellular gentamicin resistant bacteria following 1 hr of ...
Olivier Disson (7017), Marc Lecuit (40824), Yu-Huan Tsai (207946), Hélène Bierne (256713)   +3 more
core   +1 more source

InlA^m mediates mouse Ncad-dependent internalization. [PDF]

, 2013
(A) Mouse CT26 cells were transfected with scrambled siRNAs or mNcad-specific siRNAs. Bacteria internalization was evaluated by counting intracellular gentamicin resistant bacteria. Values are expressed as a mean + SD (n = 3).
Olivier Disson (7017), Marc Lecuit (40824), Yu-Huan Tsai (207946), Hélène Bierne (256713)   +3 more
core   +1 more source

Molecular detection of Listeria monocytogenes from aborted women [PDF]

Journal of Bioscience and Applied Research
Abortion, an involuntary and spontaneous termination of pregnancy, can be influenced by various factors, including potentially unknown ones. Bacterial infections play a significant role in some cases.
Rahma majid Kamel, Manar Alyassiry, Hadeel Jabar Neam, Rashad imad kadhim, Noor Alhuda Ahmed   +4 more
doaj   +1 more source

Laplace approximation for conditional autoregressive models for spatial data of diseases

MethodsX, 2022
Conditional autoregressive (CAR) distributions are used to account for spatial autocorrelation in small areal or lattice data to assess the spatial risks of diseases.
Guiming Wang
doaj   +1 more source

Bayesian Multivariate Spatial Models for Lattice Data with INLA

Journal of Statistical Software, 2021
The INLAMSM package for the R programming language provides a collection of multivariate spatial models for lattice data that can be used with the INLA package for Bayesian inference. The multivariate spatial models implemented include different struc-tures to model the spatial variation of the variables and the between-variables variability.
Palmí-Perales, Francisco, Gómez-Rubio, Virgilio, Martinez-Beneito, Miguel A.   +2 more
openaire   +4 more sources

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, Roger S. Bivand, Håvard Rue   +2 more
doaj   +1 more source