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inlabru
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", "2.11.1")
Attach the package and use:
library("inlabru")
Maintained by
Finn Lindgren
[Scholar Profile | Author Map]
[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 2.11.1, https://cran.r-project.org/web/packages/inlabru. Accessed 07 Nov. 2024.
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)
Other packages that cited inlabru R package
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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
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