inlabru - Bayesian Latent Gaussian Modelling using INLA and Extensions

Facilitates spatial and general latent Gaussian modeling using integrated nested Laplace approximation via the INLA package (<https://www.r-inla.org>). Additionally, extends the GAM-like model class to more general nonlinear predictor expressions, and implements a log Gaussian Cox process likelihood for modeling univariate and spatial point processes based on ecological survey data. Model components are specified with general inputs and mapping methods to the latent variables, and the predictors are specified via general R expressions, with separate expressions for each observation likelihood model in multi-likelihood models. A prediction method based on fast Monte Carlo sampling allows posterior prediction of general expressions of the latent variables. Ecology-focused introduction in Bachl, Lindgren, Borchers, and Illian (2019) <doi:10.1111/2041-210X.13168>.

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cpp

13.48 score 126 stars 7 dependents 1.2k scripts 3.9k downloads

fmesher - Triangle Meshes and Related Geometry Tools

Generate planar and spherical triangle meshes, compute finite element calculations for 1-, 2-, and 3-dimensional flat and curved manifolds with associated basis function spaces, methods for lines and polygons, and transparent handling of coordinate reference systems and coordinate transformation, including 'sf' and 'sp' geometries. The core 'fmesher' library code was originally part of the 'INLA' package, and implements parts of "Triangulations and Applications" by Hjelle and Daehlen (2006) <doi:10.1007/3-540-33261-8>.

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cpp

12.40 score 21 stars 32 dependents 651 scripts 11k downloads

INLAspacetime - Spatial and Spatio-Temporal Models using 'INLA'

Prepare objects to implement models over spatial and spacetime domains with the 'INLA' package (<https://www.r-inla.org>). These objects contain data to for the 'cgeneric' interface in 'INLA', enabling fast parallel computations. We implemented the spatial barrier model, see Bakka et. al. (2019) <doi:10.1016/j.spasta.2019.01.002>, and some of the spatio-temporal models proposed in Lindgren et. al. (2024) <https://raco.cat/index.php/SORT/article/view/428665>. Details are provided in the available vignettes and from the URL bellow.

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openblas

7.58 score 8 stars 102 scripts 1.9k downloads

excursions - Excursion Sets and Contour Credibility Regions for Random Fields

Functions that compute probabilistic excursion sets, contour credibility regions, contour avoiding regions, and simultaneous confidence bands for latent Gaussian random processes and fields. The package also contains functions that calculate these quantities for models estimated with the INLA package. The main references for excursions are Bolin and Lindgren (2015) <doi:10.1111/rssb.12055>, Bolin and Lindgren (2017) <doi:10.1080/10618600.2016.1228537>, and Bolin and Lindgren (2018) <doi:10.18637/jss.v086.i05>. These can be generated by the citation function in R.

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gslcppopenmp

7.22 score 8 stars 1 dependents 57 scripts 338 downloads

dirinla - Hierarchical Bayesian Dirichlet regression models using Integrated Nested Laplace Approximation

The R-package dirinla allows the user to fit models in the compositional data context. In particular, it allows fit Dirichlet regression models using the Integrated Nested Laplace Approximation (INLA) methodology.

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3.51 score 5 stars 13 scripts