Other packages > Find by keyword >

inlabru  

Bayesian Latent Gaussian Modelling using INLA and Extensions
View on CRAN: Click here


Download and install inlabru package within the R console
Install from CRAN:
install.packages("inlabru")

Install from Github:
library("remotes")
install_github("cran/inlabru")

Install by package version:
library("remotes")
install_version("inlabru", "2.13.0")



Attach the package and use:
library("inlabru")
Maintained by
Finn Lindgren
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-11-10
Latest Update: 2025-07-09
Description:
Facilitates spatial and general latent Gaussian modeling using integrated nested Laplace approximation via the INLA package (). 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) .
How to cite:
Finn Lindgren (2017). inlabru: Bayesian Latent Gaussian Modelling using INLA and Extensions. R package version 2.13.0, https://cran.r-project.org/web/packages/inlabru. Accessed 25 Jun. 2026.
Previous versions and publish date:
2.1.1 (2017-11-10 19:16), 2.1.2 (2017-11-14 17:38), 2.1.3 (2018-02-11 15:26), 2.1.9 (2018-07-24 11:20), 2.1.12 (2019-06-24 11:10), 2.1.13 (2020-02-16 23:10), 2.3.0 (2021-03-16 09:50), 2.3.1 (2021-03-23 00:00), 2.4.0 (2021-12-19 02:50), 2.5.0 (2022-03-21 16:50), 2.5.2 (2022-03-30 18:20), 2.5.3 (2022-09-05 09:20), 2.6.0 (2022-10-24 11:55), 2.7.0 (2022-12-02 10:50), 2.8.0 (2023-06-20 16:10), 2.9.0 (2023-08-28 19:40), 2.10.0 (2023-10-29 06:10), 2.10.1 (2023-12-21 02:10), 2.11.1 (2024-07-02 01:30), 2.12.0 (2024-11-21 19:30), 2.13.0 (2025-07-09 23:20), 2.14.0 (2026-03-08 07:10)
Other packages that cited inlabru R package
View inlabru citation profile
Other R packages that inlabru depends, imports, suggests or enhances
Complete documentation for inlabru
Functions, R codes and Examples using the inlabru R package
Some associated functions: Poisson1_1D . Poisson2_1D . Poisson3_1D . add_mappers . bincount . bm_list . bru . bru_call_options . bru_compute_linearisation . bru_convergence_plot . bru_env_get . bru_fill_missing . bru_get_mapper . bru_info . bru_int_polygon . bru_like_methods . bru_log . bru_log_bookmark . bru_log_message . bru_log_new . bru_log_offset . bru_log_reset . bru_make_stack . bru_mapper . bru_mapper_aggregate . bru_mapper_collect . bru_mapper_const . bru_mapper_factor . bru_mapper_fm_mesh_1d . bru_mapper_fm_mesh_2d . bru_mapper_generics . bru_mapper_harmonics . bru_mapper_index . bru_mapper_linear . bru_mapper_logsumexp . bru_mapper_marginal . bru_mapper_matrix . bru_mapper_mesh_B . bru_mapper_multi . bru_mapper_pipe . bru_mapper_scale . bru_mapper_shift . bru_mapper_summary . bru_mapper_taylor . bru_model . bru_options . bru_safe_inla . bru_safe_sp . bru_standardise_names . bru_summarise . bru_timings_plot . bru_transformation . bru_used . bru_used_update . bru_used_vars . code.components . comp_lin_eval . component . component_eval . component_list . cprod . deltaIC . devel.cvmeasure . eval_in_data_context . eval_spatial . evaluate_comp_lin . evaluate_comp_simple . evaluate_comp_simple_list_subsetting . evaluate_effect . evaluate_index . evaluate_inputs . evaluate_model . evaluate_predictor . expand_labels . extract_property . generate . gg.RasterLayer . gg.SpatRaster . gg.SpatialGridDataFrame . gg.SpatialLines . gg.SpatialPixels . gg.SpatialPixelsDataFrame . gg.SpatialPoints . gg.SpatialPolygons . gg.bru_prediction . gg.data.frame . gg.inla.mesh.1d . gg.inla.mesh . gg.matrix . gg . gg.sf . globe . glplot . gm . gmap . gorillas . gorillas_sf . iinla . index_eval . inla.stack.mjoin . inla_subset_eval . inlabru-deprecated . inlabru-package . input_eval . integration_weight_aggregation . ipoints . lgcp . like . local_testthat . materncov.bands . mexdolphin . mexdolphin_sf . mrsea . multiplot . parse_inclusion . pcmatern_B . pixels . plot.bru . plot.bru_prediction . plotsample . point2count . predict.bru . reexports . robins_subset . row_kron . sample.lgcp . seals . shrimp . sline . spatial.to.ppp . spde.posterior . spoly . summary.bru . summary.bru_options . summary.component . toygroups . 
Some associated R codes: 0_inlabru_envir.R . bru.gof.R . bru.inference.R . bru.integration.R . bru.spatial.R . data.Poisson1_1D.R . data.Poisson2_1D.R . data.Poisson3_1D.R . data.gorillas.R . data.mexdolphin.R . data.mrsea.R . data.robins_subset.R . data.seals.R . data.shrimp.R . data.toygroups.R . deltaIC.R . deprecated.R . effect.R . environment.R . fmesher.R . ggplot.R . inla.R . inlabru-package.R . integration.R . local_testthat.R . mappers.R . mesh.R . model.R . nlinla.R . plotsample.R . rgl.R . sampling.R . spatstat.R . spde.R . stack.R . track_plotting.R . transformation.R . utils.R .  Full inlabru package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
airGRiwrm  
'airGR' Integrated Water Resource Management
Semi-distributed Precipitation-Runoff Modelling based on 'airGR' package models integrating human i ...
Download / Learn more Package Citations See dependency  
sitmo  
Parallel Pseudo Random Number Generator (PPRNG) 'sitmo' Header Files
Provided within are two high quality and fast PPRNGs that may be used in an 'OpenMP' parallel enviro ...
Download / Learn more Package Citations See dependency  
edeaR  
Exploratory and Descriptive Event-Based Data Analysis
Exploratory and descriptive analysis of event based data. Provides methods for describing and select ...
Download / Learn more Package Citations See dependency  
foster  
Forest Structure Extrapolation with R
Set of tools to streamline the modeling of the relationship betweensatellite imagery time series or ...
Download / Learn more Package Citations See dependency  

27,535

R Packages

236,180

Dependencies

73,223

Author Associations

27,536

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA