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", "2.12.0")



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: 2023-08-28
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 2.12.0, https://cran.r-project.org/web/packages/inlabru. Accessed 18 Feb. 2025.
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)
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
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

r2resize  
In-Text Resize for Images, Tables and Fancy Resize Containers in 'shiny', 'rmarkdown' and 'quarto' Documents
Automatic resizing toolbar for containers, images and tables. Various resizable or expandable contai ...
Download / Learn more Package Citations See dependency  
RobustBayesianCopas  
Robust Bayesian Copas Selection Model
Fits the robust Bayesian Copas (RBC) selection model of Bai et al. (2020) for cor ...
Download / Learn more Package Citations See dependency  
MOSS  
Multi-Omic Integration via Sparse Singular Value Decomposition
High dimensionality, noise and heterogeneity among samples and features challenge the omic integrat ...
Download / Learn more Package Citations See dependency  
OptGS  
Near-Optimal Group-Sequential Designs for Continuous Outcomes
Optimal group-sequential designs minimise some function of the expected and maximum sample size whil ...
Download / Learn more Package Citations See dependency  
clustMixType  
k-Prototypes Clustering for Mixed Variable-Type Data
Functions to perform k-prototypes partitioning clustering for mixed variable-type data according to ...
Download / Learn more Package Citations See dependency  
ppmf  
Read Census Privacy Protected Microdata Files
Implements data processing described in to align modern differentially ...
Download / Learn more Package Citations See dependency  

23,712

R Packages

205,795

Dependencies

64,332

Author Associations

23,631

Publication Badges

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