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"1-Dimensional NonHomogeneous Poisson example.", "object": "Poisson2_1D", "class": [ "function" ], "fields": [], "table": false, "tojson": true }, { "name": "lambda3_1D", "title": "1-Dimensional NonHomogeneous Poisson example.", "object": "Poisson3_1D", "class": [ "function" ], "fields": [], "table": false, "tojson": true }, { "name": "mexdolphin_sf", "title": "Pan-tropical spotted dolphins in the Gulf of Mexico", "object": "mexdolphin_sf", "class": [ "list" ], "fields": [], "table": false, "tojson": false }, { "name": "mrsea", "title": "Marine renewables strategic environmental assessment", "object": "mrsea", "class": [ "list" ], "fields": [], "table": false, "tojson": false }, { "name": "pts1", "title": "1-Dimensional Homogeneous Poisson example.", "object": "Poisson1_1D", "class": [ "data.frame" ], "fields": [ "x" ], "rows": 116, "table": true, "tojson": true }, { "name": "pts2", "title": "1-Dimensional NonHomogeneous Poisson example.", "object": "Poisson2_1D", "class": [ 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[], "table": false, "tojson": false } ], "_help": [ { "page": "inlabru-package", "title": "inlabru", "topics": [ "inlabru-package", "inlabru" ] }, { "page": "as_bru_comp", "title": "Conversion methods for 'bru_comp' and 'bru_comp_list' objects", "topics": [ "as_bru_comp", "as_bru_comp.bru_comp", "as_bru_comp_list", "as_bru_comp_list.bru", "as_bru_comp_list.bru_comp", "as_bru_comp_list.bru_comp_list", "as_bru_comp_list.bru_info", "as_bru_comp_list.bru_model", "as_bru_comp_list.formula", "as_bru_comp_list.list" ] }, { "page": "as_bru_mapper", "title": "Methods for mapper extraction", "topics": [ "as_bru_mapper", "as_bru_mapper.bru_comp", "as_bru_mapper.bru_mapper", "as_bru_mapper.bru_subcomp" ] }, { "page": "as_bru_obs", "title": "Conversion methods for 'bru_obs' and 'bru_obs_list' objects", "topics": [ "as_bru_obs", "as_bru_obs.bru_obs", "as_bru_obs_list", "as_bru_obs_list.bru", "as_bru_obs_list.bru_info", "as_bru_obs_list.bru_model", "as_bru_obs_list.bru_obs", 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"bru_mapper.fm_mesh_1d" ] }, { "page": "bm_fmesher", "title": "Mapper for general 'fmesher' function space objects", "concept": [ "mappers" ], "topics": [ "bm_fmesher", "bru_mapper.fm_mesh_2d", "bru_mapper_fmesher" ] }, { "page": "bm_harmonics", "title": "Mapper for cos/sin functions", "concept": [ "mappers" ], "topics": [ "bm_harmonics", "bru_mapper_harmonics" ] }, { "page": "bm_index", "title": "Mapper for indexed variables", "concept": [ "mappers" ], "topics": [ "bm_index", "bru_mapper_index" ] }, { "page": "bm_linear", "title": "Mapper for a linear effect", "concept": [ "mappers" ], "topics": [ "bm_linear", "bru_mapper_linear" ] }, { "page": "bm_list", "title": "Methods for mapper lists", "topics": [ "as_bm_list", "as_bm_list.bm_list", "as_bm_list.bru_comp_list", "as_bm_list.list", "bm_list", "c.bm_list", "c.bru_mapper", "[.bm_list" ] }, { "page": "bm_logitaverage", "title": "Mapper for logit-sum-inverse-logit aggregation", "concept": [ "mappers" ], "topics": [ "bm_logitaverage" ] }, { "page": "bm_logsumexp", "title": "Mapper for log-sum-exp aggregation", "concept": [ "mappers" ], "topics": [ "bm_logsumexp", "bru_mapper_logsumexp" ] }, { "page": "bm_marginal", "title": "Mapper for marginal distribution transformation", "concept": [ "mappers" ], "topics": [ "bm_marginal", "bru_mapper_marginal" ] }, { "page": "bm_matrix", "title": "Mapper for matrix multiplication", "concept": [ "mappers" ], "topics": [ "bm_matrix", "bru_mapper_matrix" ] }, { "page": "bm_multi", "title": "Mapper for tensor product domains", "concept": [ "mappers" ], "topics": [ "bm_multi", "bru_mapper_multi", "[.bm_multi", "[.bru_mapper_multi" ] }, { "page": "bm_pipe", "title": "Mapper for linking several mappers in sequence", "concept": [ "mappers" ], "topics": [ "bm_pipe", "bru_mapper_pipe" ] }, { "page": "bm_reparam", "title": "Mapper for reparameterising mapper states", "concept": [ "mappers" ], "topics": [ "bm_reparam" ] }, { "page": "bm_repeat", "title": "Mapper for repeating a mapper", "concept": [ "mappers" ], "topics": [ "bm_repeat", "bru_mapper_repeat" ] }, { "page": "bm_scale", "title": "Mapper for element-wise scaling", "concept": [ "mappers" ], "topics": [ "bm_scale", "bru_mapper_scale" ] }, { "page": "bm_shift", "title": "Mapper for element-wise shifting", "concept": [ "mappers" ], "topics": [ "bm_shift", "bru_mapper_shift" ] }, { "page": "bm_sum", "title": "Mapper for adding multiple mappers", "concept": [ "mappers" ], "topics": [ "bm_sum", "bru_mapper_sum", "[.bm_sum", "[.bru_mapper_sum" ] }, { "page": "bm_taylor", "title": "Mapper for linear Taylor approximations", "concept": [ "mappers" ], "topics": [ "bm_taylor", "bru_mapper_taylor" ] }, { "page": "bru", "title": "Convenient model fitting using (iterated) INLA", "topics": [ "bru", "bru_rerun", "print.bru", "print.summary_bru", "summary.bru" ] }, { "page": "bru_block_gcpo", "title": "Extract block-averaged GCPO scores from one or more fitted bru models", "topics": [ "bru_block_gcpo" ] }, { "page": "bru_comp", "title": "Latent model component construction", "concept": [ "component constructors" ], "topics": [ "bru_comp", "bru_comp.character", "bru_component", "component" ] }, { "page": "bru_comp_env_extra", "title": "Get/set component environment data", "topics": [ "bru_comp_env", "bru_comp_env<-", "bru_comp_env_extra", "bru_comp_env_extra<-" ] }, { "page": "bru_comp_eval", "title": "Evaluate component values in predictor expressions", "topics": [ "bru_component_eval", "bru_comp_eval" ] }, { "page": "bru_comp_list", "title": "Methods for inlabru component lists", "concept": [ "component constructors" ], "topics": [ "bru_component_list", "bru_comp_list", "bru_comp_list.bru_comp", "bru_comp_list.bru_comp_list", "bru_comp_list.formula", "bru_comp_list.list", "c.bru_comp", "c.bru_comp_list", "component_list", "[.bru_comp_list" ] }, { "page": "bru_convergence_plot", "title": "Plot inlabru convergence diagnostics", "topics": [ "bru_convergence_plot" ] }, { "page": "bru_fill_missing", "title": "Fill in missing values in Spatial grids", "topics": [ "bru_fill_missing" ] }, { "page": "bru_gcpo_table", "title": "Compare block-averaged GCPO scores across multiple fitted bru models", "topics": [ "bru_gcpo_table" ] }, { "page": "bru_get_mapper", "title": "Extract mapper information from INLA model component objects", "concept": [ "mappers" ], "topics": [ "bru_get_mapper", "bru_get_mapper.inla.cgeneric", "bru_get_mapper.inla.rgeneric", "bru_get_mapper.inla.spde", "bru_get_mapper.inla_model_reparam", "bru_get_mapper_safely" ] }, { "page": "bru_index", "title": "Extract predictor or component index information", "topics": [ "bru_index", "bru_index.bru", "bru_index.bru_comp", "bru_index.bru_comp_list", "bru_index.bru_info", "bru_index.bru_model", "bru_index.bru_obs", "bru_index.bru_obs_list", "index_eval" ] }, { "page": "bru_info", "title": "Methods for bru_info objects", "topics": [ "as_bru_info", "as_bru_info.bru", "as_bru_info.bru_info", "bru_info", "bru_info.bru", "bru_info.character", "print.bru_info", "print.summary_bru_info", "summary.bru_info" ] }, { "page": "bru_input", "title": "Store and evaluate component inputs", "topics": [ "bru_input", "bru_input.bm_collect", "bru_input.bm_multi", "bru_input.bm_pipe", "bru_input.bm_repeat", "bru_input.bm_sum", "bru_input.bru_comp", "bru_input.bru_comp_list", "bru_input.bru_input", "bru_input.bru_mapper", "bru_input.bru_model", "bru_input.bru_obs", "bru_input.bru_obs_list", "new_bru_input" ] }, { "page": "bru_is_additive", "title": "Check for predictor expression additivity", "topics": [ "bru_is_additive", "bru_is_additive.bru_obs", "bru_is_additive.bru_obs_list", "bru_is_additive.bru_pred_expr", "bru_is_additive.character", "bru_is_additive.expression", "bru_is_additive.formula" ] }, { "page": "bru_is_linear", "title": "Check for predictor linearity", "topics": [ "bru_is_linear", "bru_is_linear.bru", "bru_is_linear.bru_comp", "bru_is_linear.bru_comp_list", "bru_is_linear.bru_info", "bru_is_linear.bru_mapper", "bru_is_linear.bru_model", "bru_is_linear.bru_obs", "bru_is_linear.bru_obs_list", "bru_is_linear.bru_pred_expr" ] }, { "page": "bru_is_rowwise", "title": "Check for predictor rowwise evaluability", "topics": [ "bru_is_rowwise", "bru_is_rowwise.bru_comp", "bru_is_rowwise.bru_comp_list", "bru_is_rowwise.bru_mapper", "bru_is_rowwise.bru_obs", "bru_is_rowwise.bru_obs_list", "bru_is_rowwise.bru_pred_expr" ] }, { "page": "bru_log", "title": "Access methods for 'bru_log' objects", "concept": [ "inlabru log methods" ], "topics": [ "as.character.bru_log", "bru_log", "bru_log.bru", "bru_log.bru_log", "bru_log.character", "bru_log.iinla", "c.bru_log", "format.bru_log", "length.bru_log", "print.bru_log", "[.bru_log" ] }, { "page": "bru_log_bookmark", "title": "Methods for 'bru_log' bookmarks", "concept": [ "inlabru log methods" ], "topics": [ "bru_log_bookmark", "bru_log_bookmarks" ] }, { "page": "bru_log_message", "title": "Add a log message", "concept": [ "inlabru log methods" ], "topics": [ "bru_log_abort", "bru_log_message", "bru_log_warn" ] }, { "page": "bru_log_new", "title": "Create a 'bru_log' object", "concept": [ "inlabru log methods" ], "topics": [ "bru_log_new" ] }, { "page": "bru_log_offset", "title": "Position methods for 'bru_log' objects", "concept": [ "inlabru log methods" ], "topics": [ "bru_log_index", "bru_log_offset" ] }, { "page": "bru_log_reset", "title": "Clear log contents", "concept": [ "inlabru log methods" ], "topics": [ "bru_log_reset" ] }, { "page": "bru_mapper", "title": "Constructors for 'bru_mapper' objects", "concept": [ "mappers" ], "topics": [ "bru_mapper", "bru_mapper_define" ] }, { "page": "bru_mapper_generics", "title": "Generic methods for bru_mapper objects", "concept": [ "mapper methods" ], "topics": [ "bru_mapper_generics" ] }, { "page": "bru_model_mapper_methods", "title": "Mapper methods for model objects", "topics": [ "bru_model_mapper_methods", "ibm_linear.bm_list", "ibm_linear.bru_comp_list", "ibm_linear.bru_model", "ibm_simplify.bm_list", "ibm_simplify.bru_comp", "ibm_simplify.bru_comp_list", "ibm_simplify.bru_model" ] }, { "page": "bru_names", "title": "Extract standardised names from a bru or inla result object", "topics": [ "bru_names", "bru_names.bru", "bru_names.inla" ] }, { "page": "bru_obs", "title": "Observation model construction for usage with 'bru()'", "topics": [ "bru_like_list", "bru_obs", "bru_obs_list", "bru_obs_list.bru_obs", "bru_obs_list.bru_obs_list", "bru_obs_list.list", "c.bru_obs", "c.bru_obs_list", "like", "like_list", "[.bru_obs_list" ] }, { "page": "bru_options", "title": "Create or update an options objects", "topics": [ "as.bru_options", "bru_options", "bru_options_check", "bru_options_default", "bru_options_get", "bru_options_reset", "bru_options_set", "bru_options_set_local" ] }, { "page": "bru_response_size", "title": "Response size queries", "topics": [ "bru_response_size", "bru_response_size.bru", "bru_response_size.bru_info", "bru_response_size.bru_obs", "bru_response_size.bru_obs_list", "bru_response_size.default", "bru_response_size.inla.surv", "bru_response_size.list" ] }, { "page": "bru_set_missing", "title": "Set missing values in observation models", "topics": [ "bru_set_missing", "bru_set_missing.bru", "bru_set_missing.bru_info", "bru_set_missing.bru_obs", "bru_set_missing.bru_obs_list", "bru_set_missing.data.frame", "bru_set_missing.default", "bru_set_missing.inla.surv", "bru_set_missing<-" ] }, { "page": "bru_timings", "title": "Extract timing information from fitted bru object", "topics": [ "bru_timings", "bru_timings.bru" ] }, { "page": "bru_timings_plot", "title": "Plot inlabru iteration timings", "topics": [ "bru_timings_plot" ] }, { "page": "bru_transformation", "title": "Transformation tools", "topics": [ "bru_forward_transformation", "bru_inverse_transformation", "bru_transformation" ] }, { "page": "deltaIC", "title": "Summarise DIC from 'lgcp' estimates.", "topics": [ "deltaIC" ] }, { "page": "devel.cvmeasure", "title": "Variance and correlations measures for prediction components", "topics": [ "devel.cvmeasure" ] }, { "page": "eval_spatial", "title": "Evaluate spatial covariates", "topics": [ "eval_spatial", "eval_spatial.sf", "eval_spatial.SpatialGridDataFrame", "eval_spatial.SpatialPixelsDataFrame", "eval_spatial.SpatialPolygonsDataFrame", "eval_spatial.SpatRaster", "eval_spatial.stars" ] }, { "page": "summary.bru_input", "title": "Summarise component inputs", "topics": [ "format.bru_input", "print.bru_input", "summary.bru_input" ] }, { "page": "bm_summary", "title": "mapper object summaries", "topics": [ "format.bm_collect", "format.bm_list", "format.bm_multi", "format.bm_pipe", "format.bm_reparam", "format.bm_repeat", "format.bm_sum", "format.bru_mapper", "print.bm_list", "print.bru_mapper", "print.summary_bru_mapper", "summary.bru_mapper" ] }, { "page": "generate", "title": "Generate samples from fitted bru models", "concept": [ "sample generators" ], "topics": [ "generate", "generate.bru" ] }, { "page": "gg", "title": "ggplot2 geomes for inlabru related objects", "concept": [ "geomes" ], "topics": [ "gg" ] }, { "page": "gg.bru_prediction", "title": "Geom for predictions", "concept": [ "geomes" ], "topics": [ "gg.bru_prediction", "gg.data.frame", "gg.prediction", "plot.bru_prediction", "plot.prediction" ] }, { "page": "gg.fm_mesh_1d", "title": "Geom for fm_mesh_1d objects", "concept": [ "geomes" ], "topics": [ "gg.fm_mesh_1d" ] }, { "page": "gg.fm_mesh_2d", "title": "Geom for fm_mesh_2d objects", "concept": [ "geomes" ], "topics": [ "gg.fm_mesh_2d" ] }, { "page": "gg.matrix", "title": "Geom for matrix", "concept": [ "geomes" ], "topics": [ "gg.matrix" ] }, { "page": "gg.RasterLayer", "title": "Geom for RasterLayer objects", "concept": [ "geomes" ], "topics": [ "gg.RasterLayer" ] }, { "page": "gg.sf", "title": "Geom helper for sf objects", "concept": [ "geomes" ], "topics": [ "gg.sf" ] }, { "page": "gg.Spatial", "title": "Geoms for sp Spatial objects", "concept": [ "geomes" ], "topics": [ "gg.Spatial", "gg.SpatialGridDataFrame", "gg.SpatialLines", "gg.SpatialPixels", "gg.SpatialPixelsDataFrame", "gg.SpatialPoints", "gg.SpatialPolygons" ] }, { "page": "gg.SpatRaster", "title": "Geom wrapper for SpatRaster objects", "concept": [ "geomes" ], "topics": [ "gg.SpatRaster" ] }, { "page": "glance.bru", "title": "Glance at a bru model fit", "topics": [ "glance.bru" ] }, { "page": "glplot", "title": "Render objects using RGL", "topics": [ "globe", "glplot", "glplot.fm_mesh_2d", "glplot.SpatialLines", "glplot.SpatialPoints" ] }, { "page": "gorillas_sf", "title": "Gorilla nesting sites in sf format", "topics": [ "gorillas_sf", "gorillas_sf_gcov", "gorillas_sp" ] }, { "page": "ibm_eval", "title": "Evaluate a mapping", "concept": [ "mapper methods" ], "topics": [ "ibm_eval", "ibm_eval.bm_aggregate", "ibm_eval.bm_collect", "ibm_eval.bm_const", "ibm_eval.bm_logitaverage", "ibm_eval.bm_logsumexp", "ibm_eval.bm_marginal", "ibm_eval.bm_multi", "ibm_eval.bm_pipe", "ibm_eval.bm_reparam", "ibm_eval.bm_repeat", "ibm_eval.bm_scale", "ibm_eval.bm_shift", "ibm_eval.bm_sum", "ibm_eval.bm_taylor", "ibm_eval.default" ] }, { "page": "ibm_eval2", "title": "Evaluate a mapper and its Jacobian", "concept": [ "mapper methods" ], "topics": [ "ibm_eval2", "ibm_eval2.bm_pipe", "ibm_eval2.default" ] }, { "page": "ibm_inla_subset", "title": "Find index subset of INLA visible states", "concept": [ "mapper methods" ], "topics": [ "ibm_inla_subset", "ibm_inla_subset.default" ] }, { "page": "ibm_input", "title": "Interface between 'bru_input' and 'bru_mapper'", "topics": [ "bm_autodetect", "ibm_input", "ibm_input_available", "ibm_input_get", "ibm_input_new", "ibm_input_set" ] }, { "page": "ibm_invalid_output", "title": "Detect invalid input to a mapper", "concept": [ "mapper methods" ], "topics": [ "ibm_invalid_output", "ibm_invalid_output.bm_collect", "ibm_invalid_output.bm_index", "ibm_invalid_output.bm_multi", "ibm_invalid_output.bm_repeat", "ibm_invalid_output.bm_sum", "ibm_invalid_output.default" ] }, { "page": "ibm_is_linear", "title": "Check if a mapper is linear/affine", "concept": [ "mapper methods" ], "topics": [ "ibm_is_linear", "ibm_is_linear.bm_collect", "ibm_is_linear.bm_multi", "ibm_is_linear.bm_sum", "ibm_is_linear.default" ] }, { "page": "ibm_is_rowwise", "title": "Check if a mapper is rowwise", "concept": [ "mapper methods" ], "topics": [ "ibm_is_rowwise", "ibm_is_rowwise.default" ] }, { "page": "ibm_jacobian", "title": "Jacobian of a mapper", "concept": [ "mapper methods" ], "topics": [ "ibm_jacobian", "ibm_jacobian.bm_aggregate", "ibm_jacobian.bm_collect", "ibm_jacobian.bm_const", "ibm_jacobian.bm_factor", "ibm_jacobian.bm_fmesher", "ibm_jacobian.bm_fm_mesh_1d", "ibm_jacobian.bm_harmonics", "ibm_jacobian.bm_index", "ibm_jacobian.bm_linear", "ibm_jacobian.bm_logitaverage", "ibm_jacobian.bm_logsumexp", "ibm_jacobian.bm_marginal", "ibm_jacobian.bm_matrix", "ibm_jacobian.bm_multi", "ibm_jacobian.bm_pipe", "ibm_jacobian.bm_reparam", "ibm_jacobian.bm_repeat", "ibm_jacobian.bm_scale", "ibm_jacobian.bm_shift", "ibm_jacobian.bm_sum", "ibm_jacobian.bm_taylor", "ibm_jacobian.default" ] }, { "page": "ibm_linear", "title": "Compute a mapper linearisation", "concept": [ "mapper methods" ], "topics": [ "ibm_linear", "ibm_linear.bm_collect", "ibm_linear.bm_multi", "ibm_linear.bm_repeat", "ibm_linear.bm_sum", "ibm_linear.bru_comp", "ibm_linear.default" ] }, { "page": "ibm_n", "title": "Size of the latent vector of a mapping", "concept": [ "mapper methods" ], "topics": [ "ibm_n", "ibm_n.bm_aggregate", "ibm_n.bm_collect", "ibm_n.bm_const", "ibm_n.bm_factor", "ibm_n.bm_fmesher", "ibm_n.bm_fm_mesh_1d", "ibm_n.bm_harmonics", "ibm_n.bm_linear", "ibm_n.bm_marginal", "ibm_n.bm_matrix", "ibm_n.bm_multi", "ibm_n.bm_pipe", "ibm_n.bm_reparam", "ibm_n.bm_repeat", "ibm_n.bm_scale", "ibm_n.bm_shift", "ibm_n.bm_sum", "ibm_n.bm_taylor", "ibm_n.default" ] }, { "page": "ibm_n_output", "title": "Output size of a mapping", "concept": [ "mapper methods" ], "topics": [ "ibm_n_output", "ibm_n_output.bm_aggregate", "ibm_n_output.bm_collect", "ibm_n_output.bm_marginal", "ibm_n_output.bm_multi", "ibm_n_output.bm_pipe", "ibm_n_output.bm_reparam", "ibm_n_output.bm_repeat", "ibm_n_output.bm_scale", "ibm_n_output.bm_shift", "ibm_n_output.bm_sum", "ibm_n_output.bm_taylor", "ibm_n_output.default" ] }, { "page": "ibm_names", "title": "Names of submapper", "concept": [ "mapper methods" ], "topics": [ "ibm_names", "ibm_names.bm_collect", "ibm_names.bm_multi", "ibm_names.bm_sum", "ibm_names.default", "ibm_names<-", "ibm_names<-.bm_collect", "ibm_names<-.bm_multi", "ibm_names<-.bm_sum", "ibm_names<-.bru_mapper_collect", "ibm_names<-.bru_mapper_multi", "ibm_names<-.bru_mapper_sum" ] }, { "page": "ibm_simplify", "title": "Simplify a mapper", "concept": [ "mapper methods" ], "topics": [ "ibm_simplify", "ibm_simplify.bm_pipe", "ibm_simplify.default" ] }, { "page": "ibm_values", "title": "Value vector for a mapping", "concept": [ "mapper methods" ], "topics": [ "ibm_values", "ibm_values.bm_aggregate", "ibm_values.bm_collect", "ibm_values.bm_const", "ibm_values.bm_factor", "ibm_values.bm_fmesher", "ibm_values.bm_fm_mesh_1d", "ibm_values.bm_linear", "ibm_values.bm_marginal", "ibm_values.bm_matrix", "ibm_values.bm_multi", "ibm_values.bm_pipe", "ibm_values.bm_reparam", "ibm_values.bm_repeat", "ibm_values.bm_scale", "ibm_values.bm_shift", "ibm_values.bm_sum", "ibm_values.bm_taylor", "ibm_values.default" ] }, { "page": "lgcp", "title": "Log Gaussian Cox process (LGCP) inference using INLA", "topics": [ "lgcp" ] }, { "page": "mexdolphin_sf", "title": "Pan-tropical spotted dolphins in the Gulf of Mexico", "topics": [ "mexdolphin_sf", "mexdolphin_sp" ] }, { "page": "mrsea", "title": "Marine renewables strategic environmental assessment", "topics": [ "mrsea" ] }, { "page": "multiplot", "title": "Multiple ggplots on a page.", "topics": [ "multiplot" ] }, { "page": "plot.bru", "title": "Plot method for posterior marginals estimated by bru", "topics": [ "plot.bru", "plotmarginal.inla" ] }, { "page": "plotsample", "title": "Create a plot sample.", "topics": [ "plotsample" ] }, { "page": "point2count", "title": "Convert a plot sample of points into one of counts.", "topics": [ "point2count" ] }, { "page": "Poisson1_1D", "title": "1-Dimensional Homogeneous Poisson example.", "topics": [ "countdata1", "E_nc1", "lambda1_1D", "Poisson1_1D", "pts1" ] }, { "page": "Poisson2_1D", "title": "1-Dimensional NonHomogeneous Poisson example.", "topics": [ "countdata2", "cov2_1D", "E_nc2", "lambda2_1D", "Poisson2_1D", "pts2" ] }, { "page": "Poisson3_1D", "title": "1-Dimensional NonHomogeneous Poisson example.", "topics": [ "countdata3a", "countdata3b", "E_nc3a", "E_nc3b", "lambda3_1D", "Poisson3_1D", "pts3" ] }, { "page": "predict.bru", "title": "Prediction from fitted bru model", "topics": [ "predict.bru" ] }, { "page": "robins_subset", "title": "robins_subset", "topics": [ "robins_subset" ] }, { "page": "sample.lgcp", "title": "Sample from an inhomogeneous Poisson process", "topics": [ "sample.lgcp" ] }, { "page": "shrimp", "title": "Blue and red shrimp in the Western Mediterranean Sea", "topics": [ "shrimp" ] }, { "page": "spde.posterior", "title": "Posteriors of SPDE hyper parameters and Matern correlation or covariance function.", "topics": [ "spde.posterior" ] }, { "page": "bru_obs_print", "title": "Summary and print methods for observation models", "topics": [ "print.bru_obs", "print.bru_obs_list", "print.summary_bru_obs", "print.summary_bru_obs_list", "summary.bru_obs", "summary.bru_obs_list" ] }, { "page": "summary.bru_options", "title": "Print inlabru options", "topics": [ "print.summary_bru_options", "summary.bru_options" ] }, { "page": "tidy.bru", "title": "Tidy a bru model fit", "topics": [ "tidy.bru" ] }, { "page": "toygroups", "title": "Simulated 1D animal group locations and group sizes", "topics": [ "toygroups" ] }, { "page": "toypoints", "title": "Simulated 2D point process data", "topics": [ "toypoints" ] } ], "_readme": "https://github.com/inlabru-org/inlabru/raw/HEAD/README.md", "_rundeps": [ "class", "classInt", "cli", "DBI", "dplyr", "e1071", "fmesher", "generics", "glue", "KernSmooth", "lattice", "lifecycle", "magrittr", "MASS", "Matrix", "MatrixModels", "pillar", "pkgconfig", "proxy", "R6", "Rcpp", "rlang", "s2", "sf", "sp", "splancs", "tibble", "tidyselect", "units", "utf8", "vctrs", "withr", "wk" ], "_sysdeps": [ { "shlib": "libstdc++", "package": "libstdc++6", "source": "gcc", "version": "14.2.0-4ubuntu2~24.04.1", "name": "c++", "homepage": "http://gcc.gnu.org/", "description": "GNU Standard C++ Library v3" } ], "_vignettes": [ { "source": "articles.Rmd", "filename": "articles.html", "title": "Articles list", "engine": "knitr::rmarkdown", "headings": [ "Package vignettes", "Package examples" ], "created": "2023-10-29 23:38:49", "modified": "2025-12-12 16:03:54", "commits": 2 }, { "source": "classes.Rmd", "filename": "classes.html", "title": "Classes and methods", "engine": "knitr::rmarkdown", "headings": [ "General classes", "Bru mapper classes" ], "created": "2025-10-01 22:02:59", "modified": "2025-10-02 11:06:14", "commits": 2 }, { "source": "component.Rmd", "filename": "component.html", "title": "Defining model components", "author": "Andy Seaton", "engine": "knitr::rmarkdown", "headings": [ "Basic component features", "What is a component design matrix?", "Mapper methods", "Mapper example: 2D SPDE", "Defining main, group, and replicate.", "inlabru-specific component types", "Shortcuts", "Intercept-like components", "Spatial covariates", "lm-style fixed effect and interaction syntax", "A function given with no arguments", "Non-linear predictors" ], "created": "2022-10-17 13:25:58", "modified": "2024-11-20 23:31:53", "commits": 9 }, { "source": "bru_mapper.Rmd", "filename": "bru_mapper.html", "title": "Devel: Customised model components with the bru_mapper system", "engine": "knitr::rmarkdown", "headings": [ "Mapper system introduction", "Mappers", "Basic mappers", "const", "linear", "index", "factor", "matrix", "harmonics", "Transformation mappers", "shift", "scale", "marginal", "aggregate", "logsumexp", "logitaverage", "Compound mappers", "collect", "multi", "pipe", "sum (from version 2.12.0.9001)", "repeat", "The core model component mapper", "Object mappers", "Model object mappers", "Special mappers", "Mapper methods", "Mappers for fmesher objects", "Customised mappers", "Example" ], "created": "2022-10-17 13:25:58", "modified": "2025-12-12 16:06:32", "commits": 27 }, { "source": "method.Rmd", "filename": "method.html", "title": "Iterative linearised INLA method", "author": "Finn Lindgren and Man Ho Suen", "engine": "knitr::rmarkdown", "headings": [ "The INLA method for linear predictors", "Approximate INLA for non-linear predictors", "$$\\ol{p}(\\bm{y}|\\bm{u},\\bm{\\theta})", "p(\\bm{y}|\\ol{\\bm{\\eta}}(\\bm{u}),\\bm{\\theta})", "p(\\bm{y}|g^{-1}[\\ol{\\bm{\\eta}}(\\bm{u})],\\bm{\\theta})\\approxp(\\bm{y}|g^{-1}[\\wt{\\bm{\\eta}}(\\bm{u})],\\bm{\\theta})", "p(\\bm{y}|\\wt{\\bm{\\eta}}(\\bm{u}),\\bm{\\theta})", "Fixed point iteration", "Line search", "Let $\\sigma_i^2 = \\mathrm{Var}_{\\bm{u}\\sim \\ol{p}(\\bm{u}|\\bm{y},\\bm{\\theta}_1)}(\\ol{\\bm{\\eta}}_i(\\bm{u}))$be the current estimate of the posterior variance for each predictor element $i$.We then define an inner product on the space of predictor vectors as$$\\langle \\bm{a},\\bm{b} \\rangle_V", "\\sum_i \\frac{a_i b_i}{\\sigma_i^2} .$$The squared norm for the difference between the predictor vectors $\\wt{\\bm{\\eta}}(\\bm{v}_\\alpha)$and $\\ol{\\bm{\\eta}}(\\bm{u}1)$,with respect to this inner product, is defined as$$| \\wt{\\bm{\\eta}}(\\bm{v}\\alpha) - \\ol{\\bm{\\eta}}(\\bm{u}_1)|^2_V", "Posterior non-linearity checks", "Whereas the inlabru optimisation method leads to an estimate where $| \\wt{\\bm{\\eta}} (\\bm{u}*) - \\ol{\\bm{\\eta}}(\\bm{u})|=0$ for a specific $\\bm{u}_$, the overall posterior approximation accuracy depends on the degree of nonlinearity in the vicinity of $\\bm{u}*$.There are two main options for evaluating this nonlinearity, using sampling from the approximate posterior distribution.The first option is$$\\begin{aligned}\\sum_i \\frac{E{\\bm{u}\\sim \\ol{p}(\\bm{u}|\\bm{y})}\\left[|\\ol{\\bm{\\eta}}_i(\\bm{u})-\\wt{\\bm{\\eta}}i(\\bm{u})|^2\\right]}{\\mathrm{Var}{\\bm{u}\\sim \\ol{p}(\\bm{u}|\\bm{y})}(\\ol{\\bm{\\eta}}_i(\\bm{u}))} ,\\end{aligned}$$which is the posterior expectation of the component-wise variance-normalised squared deviation between the non-linear and linearised predictor. Note that the normalising variance includes the variability induced by the posterior uncertainty for $\\bm{\\theta}$, whereas the $|\\cdot|V$ norm used for the line search used only the posterior mode.Another option is$$E{(\\bm{u},\\bm{\\theta})\\sim \\ol{p}(\\bm{u},\\bm{\\theta}|\\bm{y})} \\left[\\ln \\frac{\\ol{p}(\\bm{u} |\\bm{y},{\\bm{\\theta}})}{\\wt{p}(\\bm{u}|\\bm{y},{\\bm{\\theta}})}\\right]", "Accuracy", "For a given $\\bm{\\theta}$,$$\\begin{aligned}\\pKL{\\ol{p}}{\\wt{p}} &=E_{\\ol{p}}\\left[\\ln\\frac{\\ol{p}(\\bm{u}|\\bm{y},\\bm{\\theta})}{\\wt{p}(\\bm{u}|\\bm{y},\\bm{\\theta})}\\right]\\&=E_{\\ol{p}}\\left[\\ln\\frac{\\ol{p}(\\bm{y}|\\bm{u},\\bm{\\theta})}{\\wt{p}(\\bm{y}|\\bm{u},\\bm{\\theta})}\\right]", "Well-posedness and initialisation" ], "created": "2020-11-26 00:04:39", "modified": "2025-12-12 16:06:32", "commits": 13 }, { "source": "linearapprox.Rmd", "filename": "linearapprox.html", "title": "Nonlinear model approximation", "engine": "knitr::rmarkdown", "headings": [ "A small toy problem", "Latent Gaussian predictor version", "Introducing a latent Gaussian variable $u\\sim\\pN(0,1)$, the model can bereformulated as$$\\begin{aligned}\\lambda(u) &=-\\ln{1-\\Phi(u)}/\\gamma \\(y_i|u) &\\sim \\pPo(\\lambda(u))\\end{aligned}$$We will need some derivatives of $\\lambda$ with respect to $u$:$$\\begin{aligned}\\frac{\\partial\\lambda(u)}{\\partial u} &= \\frac{1}{\\gamma}\\frac{\\phi(u)}{1-\\Phi(u)}= \\lambda'(u) \\\\frac{\\partial^2\\lambda(u)}{\\partial u^2} &=", "\\frac{1}{\\gamma}\\frac{\\phi(u)}{1-\\Phi(u)}\\left(u + \\frac{\\phi(u)}{1-\\Phi(u)}\\right)", "Latent Gaussian posterior approximations", "n\\frac", "n\\frac{\\lambda'(u)^2}{\\lambda(u)}\\end{aligned}$$At the mode $u_0$, the first order derivative is zero, and$$\\begin{aligned}\\left.\\frac{\\partial^2\\ln p(u|{y_i})}{\\partial u^2}\\right|_{u=u_0}&=-1", "\\left{u_0 - \\gamma\\lambda'(u_0) + \\frac{\\lambda'(u_0)}{\\lambda(u_0)}\\right}u_0", "n\\frac{\\lambda'(u_0)^2}{\\lambda(u_0)} .\\end{aligned}$$The quadratic approximation of the log-posterior density at the mode $u_0$ is then$$\\ln \\breve{p}(u|{y_i}) = \\text{const} - \\frac{(u-u_0)^2}{2}\\left[", "\\left.\\frac{\\partial^2\\ln p(u|{y_i})}{\\partial u^2}\\right|{u=u_0}\\right]$$In inlabru, the approximation first linearises $\\ln \\lambda(u)$ at $u_0$ before applyingthe Taylor approximation of $\\ln p(u|{y_i})$. The linearised log-predictor is$$\\ln \\ol{\\lambda}(u) = \\ln \\lambda(u_0) + \\frac{\\lambda'(u_0)}{\\lambda(u_0)}(u - u_0)$$so that$$\\ol{\\lambda}'(u) = \\frac{\\lambda'(u_0)}{\\lambda(u_0)} \\ol{\\lambda}(u)$$and the second order derivative of the linearised log-posterior density is$$\\begin{aligned}\\left.\\frac{\\partial^2\\ln \\ol{p}(u|{y_i})}{\\partial u^2}\\right|{u=u_0}&=-1", "Posterior densities", "Posterior CDFs" ], "created": "2021-01-08 18:47:58", "modified": "2026-04-14 12:47:30", "commits": 8 }, { "source": "prediction_scores.Rmd", "filename": "prediction_scores.html", "title": "Prediction scores", "author": "Finn Lindgren", "engine": "knitr::rmarkdown", "headings": [ "Proper posterior prediction scores", "A basic score, and motivating remarks", "Proper and strictly proper scores", "Examples", "Improper scores", "Mean error/score", "Poisson model example", "Moment scores", "Log-Probability and log-density scores", "CRPS", "$$\\wh{r}{ik} = \\frac{1}{N\\text{samples}} \\sum_{j=1}^{N_\\text{samples}}{\\pP(Y\\leq k|\\lambda^{(j)}_i)", "Normal model example", "Moment scores and log-score", "Posterior expectation of conditional scores", "If we instead take advantage of the new expression above, we have$$[y - \\pE(\\lambda|\\text{data})]^2", "\\pE_{\\lambda|\\text{data}}[(y - \\lambda)^2]", "An alternative estimator for CRPS" ], "created": "2022-10-17 13:25:58", "modified": "2025-12-02 13:44:52", "commits": 21 } ], "_score": 13.516848047024094, "_indexed": true, "_nocasepkg": "inlabru", "_universes": [ "inlabru-org", "finnlindgren" ], "_previous": "2.14.1.9005", "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "2.14.1.9006", "date": "2026-06-04T11:09:42.000Z", "distro": "noble", "arch": "aarch64", "commit": "98b997b45e38bd2afd086f4c57250395f8f0ccde", "fileid": "f904a58742666cf291c2b215b8d71a2aa8aaa43b25337fe0bfe4b80bf36f8a73", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/inlabru-org/actions/runs/26947667874" }, { "r": "4.7.0", "os": "linux", "version": "2.14.1.9006", "date": "2026-06-04T11:09:56.000Z", "distro": "noble", "arch": "x86_64", "commit": "98b997b45e38bd2afd086f4c57250395f8f0ccde", "fileid": "02c1a7d8ba8dd1b1e86027a6ad35b82e2d1ad04edee4989ae49c66f0b0267fc7", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/inlabru-org/actions/runs/26947667874" }, { "r": "4.6.0", "os": "linux", "version": "2.14.1.9006", "date": "2026-06-04T11:09:46.000Z", "distro": "noble", "arch": "aarch64", "commit": "98b997b45e38bd2afd086f4c57250395f8f0ccde", "fileid": "b92742faec9b067207c8b4483cfa698a59d75976f3b25205a0070c1bfaa76453", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/inlabru-org/actions/runs/26947667874" }, { "r": "4.6.0", "os": "linux", "version": "2.14.1.9006", "date": "2026-06-04T11:10:06.000Z", "distro": "noble", "arch": "x86_64", "commit": "98b997b45e38bd2afd086f4c57250395f8f0ccde", "fileid": "96651efb1274be6fc3d5b163c74dd437c909f6a36dded3e86feebe5a55b94534", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/inlabru-org/actions/runs/26947667874" }, { "r": "4.5.3", "os": "mac", "version": "2.14.1.9006", "date": "2026-06-04T11:13:48.000Z", "arch": "aarch64", "commit": "98b997b45e38bd2afd086f4c57250395f8f0ccde", "fileid": "511fec81eba58176643db1472880cf52d859ee85f141d67bbcf9c03851d680f1", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/inlabru-org/actions/runs/26947667874" }, { "r": "4.5.3", "os": "mac", "version": "2.14.1.9006", "date": "2026-06-04T11:14:01.000Z", "arch": "x86_64", "commit": "98b997b45e38bd2afd086f4c57250395f8f0ccde", "fileid": "01194b164f6c4796943badad577890bd4259b294e69fc2b1e1f9732e5102f5a0", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/inlabru-org/actions/runs/26947667874" }, { "r": "4.6.0", "os": "mac", "version": "2.14.1.9006", "date": "2026-06-04T11:09:18.000Z", "arch": "aarch64", "commit": "98b997b45e38bd2afd086f4c57250395f8f0ccde", "fileid": "162aa24b16b1a489e417faf8466105b8e3cbb849250a1b4fd7c872b1b7ffb5d8", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/inlabru-org/actions/runs/26947667874" }, { "r": "4.6.0", "os": "mac", "version": "2.14.1.9006", "date": "2026-06-04T11:10:55.000Z", "arch": "x86_64", "commit": "98b997b45e38bd2afd086f4c57250395f8f0ccde", "fileid": "3b8206d52b8f9c88a58727f51265f506766d244692d971e63dcb6bb1198511df", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/inlabru-org/actions/runs/26947667874" }, { "r": "4.6.0", "os": "wasm", "version": "2.14.1.9006", "date": "2026-06-04T11:09:55.000Z", "arch": "emscripten", "commit": "98b997b45e38bd2afd086f4c57250395f8f0ccde", "fileid": "63a858e944109e603b83c3d4d67d32e5b5cdaa2221ed98353080a39546d31ba6", "status": "success", "buildurl": "https://github.com/r-universe/inlabru-org/actions/runs/26947667874" }, { "r": "4.7.0", "os": "win", "version": "2.14.1.9006", "date": "2026-06-04T11:08:55.000Z", "arch": "x86_64", "commit": "98b997b45e38bd2afd086f4c57250395f8f0ccde", "fileid": "063a6f50352d2e9af453edcde202dcde15cf53eac097df3dfac901d17b521da5", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/inlabru-org/actions/runs/26947667874" }, { "r": "4.5.3", "os": "win", "version": "2.14.1.9006", "date": "2026-06-04T11:08:24.000Z", "arch": "x86_64", "commit": "98b997b45e38bd2afd086f4c57250395f8f0ccde", "fileid": "4e33370cfb89fccc36a75b69cbe3808938060d34851fa906dca9074e17cfa024", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/inlabru-org/actions/runs/26947667874" }, { "r": "4.6.0", "os": "win", "version": "2.14.1.9006", "date": "2026-06-04T11:08:43.000Z", "arch": "x86_64", "commit": "98b997b45e38bd2afd086f4c57250395f8f0ccde", "fileid": "03f395579c482acddb40538daf2b25140803a0eda4df2d93051fbf8944f9f05f", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/inlabru-org/actions/runs/26947667874" } ] }