Package index • inlabru

Model construction and estimation

Functions for constructing models and performing 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_index() experimental: Extract predictor index information

Posterior evaluation

Functions for evaluating posterior properties.

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

Accessing the optimization text log, and plotting the optimization convergence.

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

Functions for bru_mapper handling.

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

Miscellaneous functions.

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

Functions for helping build figures.

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

Functions for printing.

format(<bru_mapper>) 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>): 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

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

Helper functions for more low level operations.

evaluate_effect_single_state(): Evaluate a component effect

evaluate_index(): Compute all index values

evaluate_inputs(): Compute all component inputs

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

Deprecated methods

multiplot() deprecated: Multiple ggplots on a page.