Package index
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inlabru-packageinlabru - inlabru
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bru()bru_rerun()print(<bru>) - Convenient model fitting using (iterated) INLA
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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()
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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
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bru_comp()bru_component() - Latent model component construction
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bru_comp_eval() - Evaluate component values in predictor expressions
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bru_comp_list()c(<bru_comp_list>)c(<bru_comp>)`[`(<bru_comp_list>) - Methods for inlabru component lists
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lgcp() - Log Gaussian Cox process (LGCP) inference using INLA
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bru_response_size() - Response size queries
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bru_set_missing() - Set missing values in observation models
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bru_names() - Extract standardised names from a bru or inla result object
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generate() - Generate samples from fitted bru models
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predict(<bru>) - Prediction from fitted bru model
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spde.posterior() - Posteriors of SPDE hyper parameters and Matern correlation or covariance function.
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deltaIC() - Summarise DIC and WAIC from
lgcpobjects.
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devel.cvmeasure() - Variance and correlations measures for prediction components
Optimization log information
Accessing the optimization text log, and plotting the optimization convergence.
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bru_log()format(<bru_log>)print(<bru_log>)as.character(<bru_log>)`[`(<bru_log>)c(<bru_log>)length(<bru_log>) - Access methods for
bru_logobjects
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bru_log_bookmark()bru_log_bookmarks() - Methods for
bru_logbookmarks
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bru_log_message()bru_log_abort()bru_log_warn() - Add a log message
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bru_log_new() - Create a
bru_logobject
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bru_log_offset()bru_log_index() - Position methods for
bru_logobjects
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bru_log_reset() - Clear log contents
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bru_convergence_plot() - Plot inlabru convergence diagnostics
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bru_timings() - Extract timing information from fitted bru object
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bru_timings_plot() - Plot inlabru iteration timings
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bru_get_mapper()bru_get_mapper_safely() - Extract mapper information from INLA model component objects
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bm_aggregate()bru_mapper_aggregate() - Mapper for aggregation
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bm_collect()bru_mapper_collect()`[`(<bm_collect>)`[`(<bru_mapper_collect>) - Mapper for concatenated variables
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bm_const()bru_mapper_const() - Constant mapper
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bm_factor()bru_mapper_factor() - Mapper for factor variables
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bru_mapper(<fm_mesh_1d>) - Mapper for
fm_mesh_1d
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bm_fmesher()bru_mapper_fmesher()bru_mapper(<fm_mesh_2d>) - Mapper for general
fmesherfunction space objects
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bm_harmonics()bru_mapper_harmonics() - Mapper for cos/sin functions
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bm_index()bru_mapper_index() - Mapper for indexed variables
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bm_linear()bru_mapper_linear() - Mapper for a linear effect
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bm_logsumexp()bru_mapper_logsumexp() - Mapper for log-sum-exp aggregation
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bm_marginal()bru_mapper_marginal() - Mapper for marginal distribution transformation
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bm_matrix()bru_mapper_matrix() - Mapper for matrix multiplication
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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
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bm_multi()bru_mapper_multi()`[`(<bm_multi>)`[`(<bru_mapper_multi>) - Mapper for tensor product domains
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bm_pipe()bru_mapper_pipe() - Mapper for linking several mappers in sequence
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bm_repeat()bru_mapper_repeat() - Mapper for repeating a mapper
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bm_scale()bru_mapper_scale() - Mapper for element-wise scaling
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bm_shift()bru_mapper_shift() - Mapper for element-wise shifting
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bm_sum()bru_mapper_sum()`[`(<bm_sum>)`[`(<bru_mapper_sum>) - Mapper for adding multiple mappers
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bm_taylor()bru_mapper_taylor() - Mapper for linear Taylor approximations
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bru_mapper()bru_mapper_define() - Constructors for
bru_mapperobjects
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bru_mapper_generics - Generic methods for bru_mapper objects
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ibm_linear(<bru_model>)ibm_linear(<bru_comp_list>)ibm_simplify(<bru_model>)ibm_simplify(<bru_comp>)ibm_simplify(<bru_comp_list>)ibm_linear(<bm_list>)ibm_simplify(<bm_list>) - Mapper methods for model objects
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ibm_eval() - Evaluate a mapping
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ibm_eval2() - Evaluate a mapper and its Jacobian
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ibm_inla_subset() - Find index subset of INLA visible states
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ibm_invalid_output() - Detect invalid input to a mapper
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ibm_is_linear() - Check if a mapper is linear/affine
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ibm_jacobian() - Jacobian of a mapper
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ibm_linear() - Compute a mapper linearisation
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ibm_n() - Size of the latent vector of a mapping
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ibm_n_output() - Output size of a mapping
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ibm_names()`ibm_names<-`() - Names of submapper
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ibm_simplify() - Simplify a mapper
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ibm_values() - Value vector for a mapping
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as_bm_list()c(<bru_mapper>)c(<bm_list>)`[`(<bm_list>) - Methods for mapper lists
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bm_logitaverage()experimental - Mapper for logit-sum-inverse-logit aggregation
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as_bru_mapper() - Methods for mapper extraction
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bru_forward_transformation()bru_inverse_transformation() - Transformation tools
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eval_spatial() - Evaluate spatial covariates
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bru_fill_missing() - Fill in missing values in Spatial grids
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point2count() - Convert a plot sample of points into one of counts.
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sample.lgcp() - Sample from an inhomogeneous Poisson process
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plot(<bru>)plotmarginal.inla() - Plot method for posterior marginals estimated by bru
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plot(<bru_prediction>)plot(<prediction>) - Plot prediction using ggplot2
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plotsample() - Create a plot sample.
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globe() - Visualize a globe using RGL
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gg(<RasterLayer>) - Geom for RasterLayer objects
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gg() - ggplot2 geomes for inlabru related objects
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gg(<SpatRaster>) - Geom wrapper for SpatRaster objects
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gg(<SpatialGridDataFrame>) - Geom for SpatialGridDataFrame objects
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gg(<SpatialLines>) - Geom for SpatialLines objects
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gg(<SpatialPixels>) - Geom for SpatialPixels objects
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gg(<SpatialPixelsDataFrame>) - Geom for SpatialPixelsDataFrame objects
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gg(<SpatialPoints>) - Geom for SpatialPoints objects
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gg(<SpatialPolygons>) - Geom for SpatialPolygons objects
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gg(<bru_prediction>)gg(<prediction>) - Geom for predictions
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gg(<data.frame>) - Geom for data.frame
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gg(<fm_mesh_1d>) - Geom for fm_mesh_1d objects
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gg(<fm_mesh_2d>) - Geom for fm_mesh_2d objects
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gg(<matrix>) - Geom for matrix
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gg(<sf>) - Geom helper for sf objects
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glplot() - Render objects using RGL
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bincount() - 1D LGCP bin count simulation and comparison with data
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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
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bru()bru_rerun()print(<bru>) - Convenient model fitting using (iterated) INLA
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bru_info()summary(<bru_info>)print(<summary_bru_info>)print(<bru_info>) - Methods for bru_info objects
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bru_log()format(<bru_log>)print(<bru_log>)as.character(<bru_log>)`[`(<bru_log>)c(<bru_log>)length(<bru_log>) - Access methods for
bru_logobjects
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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
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summary(<bru>)print(<summary_bru>) - Summary for an inlabru fit
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summary(<bru_options>)print(<summary_bru_options>) - Print inlabru options
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Poisson1_1D - 1-Dimensional Homogeneous Poisson example.
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Poisson2_1D - 1-Dimensional NonHomogeneous Poisson example.
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Poisson3_1D - 1-Dimensional NonHomogeneous Poisson example.
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gorillas_sfgorillas_sf_gcov()gorillas_sp() - Gorilla nesting sites in sf format
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mexdolphin_sfmexdolphin_sp() - Pan-tropical spotted dolphins in the Gulf of Mexico
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mrsea - Marine renewables strategic environmental assessment
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robins_subset - robins_subset
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shrimp - Blue and red shrimp in the Western Mediterranean Sea
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toygroups - Simulated 1D animal group locations and group sizes
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toypoints - Simulated 2D point process data
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bru_input()bru_input_create()input_eval()evaluate_inputs() - Obtain component inputs
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evaluate_effect_single_state() - Evaluate a component effect
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evaluate_model()evaluate_state() - Evaluate or sample from a posterior result given a model and locations
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evaluate_predictor() - Evaluate component effects or expressions
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expand_labels() - Expand labels
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bru_inla.stack.mjoin() - Join stacks intended to be run with different likelihoods
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spatial.to.ppp() - Convert SpatialPoints and boundary polygon to spatstat ppp object
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bru_make_stack() - Build an inla data stack from linearisation information
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bru_summarise() - Summarise and annotate data
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bru_standardise_names() - Standardise inla hyperparameter names
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bru_safe_inla() - Load INLA safely for examples and tests
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bru_safe_sp() - Check for potential
spversion compatibility issues
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bru_call_options() - Additional bru options
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bru_compute_linearisation() - Compute inlabru model linearisation information
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bru_is_additive() - Check for predictor expression additivity
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multiplot()deprecated - Multiple ggplots on a page.