Package index

Model construction and estimation

inlabru-package inlabru

inlabru

bru() bru_rerun() print(<bru>)

Convenient model fitting using (iterated) INLA

bru_obs() like() bru_obs_list() c(<bru_obs>) c(<bru_obs_list>) `[`(<bru_obs_list>) like_list() bru_like_list()

Observation model construction for usage with bru()

bru_options() as.bru_options() bru_options_default() bru_options_check() bru_options_get() bru_options_set() bru_options_reset() bru_options_set_local()

Create or update an options objects

bru_comp() bru_component()

Latent model component construction

bru_comp_eval()

Evaluate component values in predictor expressions

bru_comp_list() c(<bru_comp_list>) c(<bru_comp>) `[`(<bru_comp_list>)

Methods for inlabru component lists

lgcp()

Log Gaussian Cox process (LGCP) inference using INLA

bru_response_size()

Response size queries

bru_set_missing()

Set missing values in observation models

Posterior evaluation

generate()

Generate samples from fitted bru models

predict(<bru>)

Prediction from fitted bru model

spde.posterior()

Posteriors of SPDE hyper parameters and Matern correlation or covariance function.

deltaIC()

Summarise DIC and WAIC from lgcp objects.

devel.cvmeasure()

Variance and correlations measures for prediction components

Optimization log information

bru_log() format(<bru_log>) print(<bru_log>) as.character(<bru_log>) `[`(<bru_log>) c(<bru_log>) length(<bru_log>)

Access methods for bru_log objects

bru_log_bookmark() bru_log_bookmarks()

Methods for bru_log bookmarks

bru_log_message() bru_log_abort() bru_log_warn()

Add a log message

bru_log_new()

Create a bru_log object

bru_log_offset() bru_log_index()

Position methods for bru_log objects

bru_log_reset()

Clear log contents

bru_convergence_plot()

Plot inlabru convergence diagnostics

bru_timings()

Extract timing information from fitted bru object

bru_timings_plot()

Plot inlabru iteration timings

Mapper methods

bru_get_mapper() bru_get_mapper_safely()

Extract mapper information from INLA model component objects

bm_aggregate() bru_mapper_aggregate() ibm_n(<bm_aggregate>) ibm_n_output(<bm_aggregate>) ibm_values(<bm_aggregate>) ibm_jacobian(<bm_aggregate>) ibm_eval(<bm_aggregate>)

Mapper for aggregation

bm_collect() bru_mapper_collect() ibm_n(<bm_collect>) ibm_n_output(<bm_collect>) ibm_values(<bm_collect>) ibm_is_linear(<bm_collect>) ibm_jacobian(<bm_collect>) ibm_eval(<bm_collect>) ibm_linear(<bm_collect>) ibm_invalid_output(<bm_collect>) `[`(<bm_collect>) `[`(<bru_mapper_collect>) ibm_names(<bm_collect>) `ibm_names<-`(<bm_collect>) `ibm_names<-`(<bru_mapper_collect>)

Mapper for concatenated variables

bm_const() bru_mapper_const() ibm_n(<bm_const>) ibm_values(<bm_const>) ibm_jacobian(<bm_const>) ibm_eval(<bm_const>)

Constant mapper

bm_factor() bru_mapper_factor() ibm_n(<bm_factor>) ibm_values(<bm_factor>) ibm_jacobian(<bm_factor>)

Mapper for factor variables

bru_mapper(<fm_mesh_1d>) ibm_n(<bm_fm_mesh_1d>) ibm_values(<bm_fm_mesh_1d>) ibm_jacobian(<bm_fm_mesh_1d>) ibm_n(<bm_inla_mesh_1d>) ibm_values(<bm_inla_mesh_1d>) ibm_jacobian(<bm_inla_mesh_1d>)

Mapper for fm_mesh_1d

bru_mapper(<fm_mesh_2d>) ibm_n(<bm_fm_mesh_2d>) ibm_values(<bm_fm_mesh_2d>) ibm_jacobian(<bm_fm_mesh_2d>) ibm_n(<bm_inla_mesh_2d>) ibm_values(<bm_inla_mesh_2d>) ibm_jacobian(<bm_inla_mesh_2d>)

Mapper for fm_mesh_2d

bm_fmesher() bru_mapper_fmesher() ibm_n(<bm_fmesher>) ibm_values(<bm_fmesher>) ibm_jacobian(<bm_fmesher>)

Mapper for general fmesher function space objects

bm_harmonics() bru_mapper_harmonics() ibm_n(<bm_harmonics>) ibm_jacobian(<bm_harmonics>)

Mapper for cos/sin functions

bm_index() bru_mapper_index() ibm_invalid_output(<bm_index>) ibm_jacobian(<bm_index>)

Mapper for indexed variables

bm_linear() bru_mapper_linear() ibm_n(<bm_linear>) ibm_values(<bm_linear>) ibm_jacobian(<bm_linear>)

Mapper for a linear effect

bm_logsumexp() bru_mapper_logsumexp() ibm_jacobian(<bm_logsumexp>) ibm_eval(<bm_logsumexp>)

Mapper for log-sum-exp aggregation

bm_marginal() bru_mapper_marginal() ibm_n(<bm_marginal>) ibm_n_output(<bm_marginal>) ibm_values(<bm_marginal>) ibm_jacobian(<bm_marginal>) ibm_eval(<bm_marginal>)

Mapper for marginal distribution transformation

bm_matrix() bru_mapper_matrix() ibm_n(<bm_matrix>) ibm_values(<bm_matrix>) ibm_jacobian(<bm_matrix>)

Mapper for matrix multiplication

bm_mesh_B() bru_mapper_mesh_B() ibm_n(<bm_mesh_B>) ibm_values(<bm_mesh_B>) ibm_jacobian(<bm_mesh_B>)

Mapper for basis conversion

bm_multi() bru_mapper_multi() ibm_n(<bm_multi>) ibm_n_output(<bm_multi>) ibm_values(<bm_multi>) ibm_is_linear(<bm_multi>) ibm_jacobian(<bm_multi>) ibm_linear(<bm_multi>) ibm_eval(<bm_multi>) ibm_invalid_output(<bm_multi>) `[`(<bm_multi>) `[`(<bru_mapper_multi>) ibm_names(<bm_multi>) `ibm_names<-`(<bm_multi>) `ibm_names<-`(<bru_mapper_multi>)

Mapper for tensor product domains

bm_pipe() bru_mapper_pipe() ibm_n(<bm_pipe>) ibm_n_output(<bm_pipe>) ibm_values(<bm_pipe>) ibm_jacobian(<bm_pipe>) ibm_eval(<bm_pipe>) ibm_eval2(<bm_pipe>) ibm_simplify(<bm_pipe>)

Mapper for linking several mappers in sequence

bm_repeat() bru_mapper_repeat() ibm_n(<bm_repeat>) ibm_n_output(<bm_repeat>) ibm_values(<bm_repeat>) ibm_jacobian(<bm_repeat>) ibm_eval(<bm_repeat>) ibm_linear(<bm_repeat>) ibm_invalid_output(<bm_repeat>)

Mapper for repeating a mapper

bm_scale() bru_mapper_scale() ibm_n(<bm_scale>) ibm_n_output(<bm_scale>) ibm_values(<bm_scale>) ibm_jacobian(<bm_scale>) ibm_eval(<bm_scale>)

Mapper for element-wise scaling

bm_shift() bru_mapper_shift() ibm_n(<bm_shift>) ibm_n_output(<bm_shift>) ibm_values(<bm_shift>) ibm_jacobian(<bm_shift>) ibm_eval(<bm_shift>)

Mapper for element-wise shifting

bm_sum() bru_mapper_sum() ibm_n(<bm_sum>) ibm_n_output(<bm_sum>) ibm_values(<bm_sum>) ibm_is_linear(<bm_sum>) ibm_jacobian(<bm_sum>) ibm_eval(<bm_sum>) ibm_linear(<bm_sum>) ibm_invalid_output(<bm_sum>) `[`(<bm_sum>) `[`(<bru_mapper_sum>) ibm_names(<bm_sum>) `ibm_names<-`(<bm_sum>) `ibm_names<-`(<bru_mapper_sum>)

Mapper for adding multiple mappers

bm_taylor() bru_mapper_taylor() ibm_n(<bm_taylor>) ibm_n_output(<bm_taylor>) ibm_values(<bm_taylor>) ibm_jacobian(<bm_taylor>) ibm_eval(<bm_taylor>)

Mapper for linear Taylor approximations

bru_mapper() bru_mapper_define()

Constructors for bru_mapper objects

ibm_n() ibm_n_output() ibm_values() ibm_is_linear() ibm_jacobian() ibm_linear() ibm_simplify() ibm_eval() ibm_eval2() ibm_names() `ibm_names<-`() ibm_inla_subset() ibm_invalid_output()

Generic methods for bru_mapper objects

as_bm_list() c(<bru_mapper>) c(<bm_list>) `[`(<bm_list>) ibm_linear(<bm_list>) ibm_simplify(<bm_list>)

Methods for mapper lists

ibm_linear(<bru_model>) ibm_linear(<bru_comp_list>) ibm_linear(<bru_comp>) ibm_simplify(<bru_model>) ibm_simplify(<bru_comp>) ibm_simplify(<bru_comp_list>)

Mapper methods for model objects

as_bru_mapper()

Methods for mapper extraction

bru_forward_transformation() bru_inverse_transformation()

Transformation tools

Miscellaneous

eval_spatial()

Evaluate spatial covariates

bru_fill_missing()

Fill in missing values in Spatial grids

point2count()

Convert a plot sample of points into one of counts.

sample.lgcp()

Sample from an inhomogeneous Poisson process

Plot helpers

plot(<bru>) plotmarginal.inla()

Plot method for posterior marginals estimated by bru

plot(<bru_prediction>) plot(<prediction>)

Plot prediction using ggplot2

plotsample()

Create a plot sample.

globe()

Visualize a globe using RGL

gg(<RasterLayer>)

Geom for RasterLayer objects

gg()

ggplot2 geomes for inlabru related objects

gg(<SpatRaster>)

Geom wrapper for SpatRaster objects

gg(<SpatialGridDataFrame>)

Geom for SpatialGridDataFrame objects

gg(<SpatialLines>)

Geom for SpatialLines objects

gg(<SpatialPixels>)

Geom for SpatialPixels objects

gg(<SpatialPixelsDataFrame>)

Geom for SpatialPixelsDataFrame objects

gg(<SpatialPoints>)

Geom for SpatialPoints objects

gg(<SpatialPolygons>)

Geom for SpatialPolygons objects

gg(<bru_prediction>) gg(<prediction>)

Geom for predictions

gg(<data.frame>)

Geom for data.frame

gg(<fm_mesh_1d>)

Geom for fm_mesh_1d objects

gg(<fm_mesh_2d>)

Geom for fm_mesh_2d objects

gg(<matrix>)

Geom for matrix

gg(<sf>)

Geom helper for sf objects

glplot()

Render objects using RGL

bincount()

1D LGCP bin count simulation and comparison with data

Printing methods

format(<bru_mapper>) format(<bm_list>) summary(<bru_mapper>) format(<bm_multi>) format(<bm_pipe>) format(<bm_collect>) format(<bm_sum>) format(<bm_repeat>) print(<summary_bru_mapper>) print(<bru_mapper>) print(<bm_list>)

mapper object summaries

bru() bru_rerun() print(<bru>)

Convenient model fitting using (iterated) INLA

bru_info() summary(<bru_info>) print(<summary_bru_info>) print(<bru_info>)

Methods for bru_info objects

bru_log() format(<bru_log>) print(<bru_log>) as.character(<bru_log>) `[`(<bru_log>) c(<bru_log>) length(<bru_log>)

Access methods for bru_log objects

summary(<bru_obs>) summary(<bru_obs_list>) print(<summary_bru_obs>) print(<summary_bru_obs_list>) print(<bru_obs>) print(<bru_obs_list>)

Summary and print methods for observation models

summary(<bru>) print(<summary_bru>)

Summary for an inlabru fit

summary(<bru_options>) print(<summary_bru_options>)

Print inlabru options

Data objects

Poisson1_1D

1-Dimensional Homogeneous Poisson example.

Poisson2_1D

1-Dimensional NonHomogeneous Poisson example.

Poisson3_1D

1-Dimensional NonHomogeneous Poisson example.

gorillas_sf gorillas_sf_gcov() gorillas_sp()

Gorilla nesting sites in sf format

mexdolphin_sf mexdolphin_sp()

Pan-tropical spotted dolphins in the Gulf of Mexico

mrsea

Marine renewables strategic environmental assessment

robins_subset

robins_subset

shrimp

Blue and red shrimp in the Western Mediterranean Sea

toygroups

Simulated 1D animal group locations and group sizes

toypoints

Simulated 2D point process data

Internal helper functions

bru_input() input_eval() evaluate_inputs()

Obtain component inputs

evaluate_effect_single_state()

Evaluate a component effect

evaluate_model() evaluate_state()

Evaluate or sample from a posterior result given a model and locations

evaluate_predictor()

Evaluate component effects or expressions

expand_labels()

Expand labels

bru_inla.stack.mjoin()

Join stacks intended to be run with different likelihoods

spatial.to.ppp()

Convert SpatialPoints and boundary polygon to spatstat ppp object

bru_make_stack()

Build an inla data stack from linearisation information

bru_summarise()

Summarise and annotate data

bru_standardise_names()

Standardise inla hyperparameter names

bru_safe_inla()

Load INLA safely for examples and tests

bru_safe_sp()

Check for potential sp version compatibility issues

bru_call_options()

Additional bru options

bru_compute_linearisation()

Compute inlabru model linearisation information

bru_is_additive()

Check for predictor expression additivity

Deprecated methods

multiplot() deprecated

Multiple ggplots on a page.