Man pages for couplr
Optimal Pairing and Matching via Linear Assignment
| animated_methods | List methods that currently support animation |
| apply_all_constraints | Apply all constraints to cost matrix |
| apply_calipers | Apply caliper constraints |
| apply_max_distance | Apply maximum distance constraint |
| apply_scaling | Apply scaling to matching variables |
| apply_weights | Apply weights to matching variables |
| as_assignment_matrix | Convert assignment result to a binary matrix |
| as_matchit | Convert couplr Result to matchit Object |
| assign_blocks_cluster | Assign blocks using clustering |
| assign_blocks_group | Assign blocks based on grouping variable(s) |
| assignment | Linear assignment solver |
| assignment_duals | Solve assignment problem and return dual variables |
| augment.matching_result | Augment Matching Results with Original Data (broom-style) |
| auto_encode_categorical | Automatically encode categorical variables |
| autoplot.balance_diagnostics | ggplot2 autoplot for balance diagnostics |
| autoplot.matching_result | ggplot2 autoplot for matching results |
| autoplot.sensitivity_analysis | ggplot2 autoplot for sensitivity analysis |
| balance_diagnostics | Balance Diagnostics for Matched Pairs |
| balance_table | Create Balance Table |
| bal.tab.matching_result | Balance Table for Matching Results (cobalt integration) |
| BIG_COST | Large value for forbidden pairs |
| bottleneck_assignment | Solve the Bottleneck Assignment Problem |
| build_cost_matrix | Build cost matrix for matching |
| calculate_var_balance | Calculate Variable-Level Balance Statistics |
| can_parallelize | Check if parallel processing is available |
| cardinality_match | Cardinality Matching |
| cem_match | Coarsened Exact Matching |
| check_cost_distribution | Check cost distribution for problems |
| check_full_matching | Check if full matching was achieved |
| check_unique_ids | Error on repeated id values |
| check_variable_health | Check variable health for matching |
| compute_distance_matrix | Compute pairwise distance matrix |
| compute_distances | Compute and Cache Distance Matrix for Reuse |
| count_valid_pairs | Count valid pairs in cost matrix |
| couplr_emoji | Get a themed emoji |
| couplr_inform | Info message with emoji |
| couplr_messages | Couplr message helpers with emoji and humor |
| couplr-package | couplr: Optimal Pairing and Matching via Linear Assignment |
| couplr_stop | Stop with a fun, themed error message |
| couplr_success | Success message with emoji |
| couplr_warn | Warn with a fun, themed warning message |
| design_estimand | What the design identifies |
| detect_blocking | Detect and validate blocking |
| diagnose_distance_matrix | Diagnose distance matrix and suggest fixes |
| dot-assignment_implicit | Solve an implicit assignment by generating the pairs it needs |
| dot-assignment_lazy | Solve a lazy_cost_spec (memory_mode = "lazy" backend for... |
| dot-auto_breaks | Compute automatic break points for CEM binning |
| dot-autoplot_hist | Histogram of |std diff| via ggplot2 |
| dot-autoplot_love | Love plot via ggplot2 |
| dot-autoplot_variance | Variance ratio plot via ggplot2 |
| dot-balance_flow_audit | Check a balance flow against the objective it is meant to... |
| dot-balance_flow_encode | The flow a matched set corresponds to |
| dot-balance_flow_problem | Compile a balance design into a flow problem |
| dot-balance_flow_read | Read a solved balance flow |
| dot-balance_node_layout | Node layout of a balance flow network |
| dot-blocks_parallel | Shared parallel block matching implementation |
| dot-cardinality_branch_bound | Branch and bound over the moment constraints |
| dot-cardinality_flow | One solve of a balance network |
| dot-cardinality_heuristic_report | Report for a pruned match |
| dot-cardinality_lagrangian | Lagrangian bound for one node |
| dot-cardinality_prune | Balance pruning heuristic |
| dot-cardinality_report | Report of a cardinality match |
| dot-cardinality_result | Assemble a matching_result from a cardinality report |
| dot-cardinality_solve | Balance-constrained cardinality match |
| dot-compute_pair_balance | Compute standardized differences for current pairs |
| dot-couples_blocked | Shared blocked matching implementation |
| dot-couples_from_distance | Shared matching from precomputed distance object |
| dot-couples_replace | Replacement matching: each left picks its best right... |
| dot-couples_single | Shared single matching implementation |
| dot-overall_balance | Summarise a per-variable balance table |
| dot-pair_var_diffs | Compute per-pair differences on a single variable |
| dot-rosenbaum_bounds | Compute Rosenbaum bounds via normal approximation |
| err_invalid_param | Invalid parameter error |
| err_missing_data | Missing data error |
| err_missing_vars | Missing variables error |
| err_no_valid_pairs | All pairs forbidden error |
| estimate_dense_matrix_mb | Estimate dense cost-matrix memory footprint in megabytes |
| estimate_dense_solve_mb | Estimate the peak footprint of a dense solve in megabytes |
| example_costs | Example cost matrices for assignment problems |
| example_df | Example assignment problem data frame |
| explain_dispatch | Explain which solver 'method = "auto"' selects, and why |
| extract_ids | Extract and standardize IDs from data frames |
| extract_matching_vars | Extract matching variables from data frame |
| filter_blocks | Filter blocks based on size and balance criteria |
| full_match | Full Matching |
| get_block_id_column | Standardize block ID column name |
| get_free_ram_mb | Estimate available system RAM in megabytes |
| get_method_used | Extract method used from assignment result |
| get_total_cost | Extract total cost from assignment result |
| greedy_blocks_parallel | Greedy match blocks in parallel |
| group_by | Re-export of dplyr::group_by |
| has_blocks | Check if data frame has blocking information |
| has_valid_pairs | Check if any valid pairs exist |
| hospital_staff | Hospital staff scheduling example dataset |
| info_low_match_rate | Low match rate info |
| is_distance_object | Check if Object is a Distance Object |
| is_lap_solve_batch_result | Check if object is a batch assignment result |
| is_lap_solve_kbest_result | Check if object is a k-best assignment result |
| is_lap_solve_result | Check if object is an assignment result |
| join_matched | Join Matched Pairs with Original Data |
| lap_animate | Animate an assignment algorithm step-by-step |
| lap_solve | Solve linear assignment problems |
| lap_solve_batch | Solve multiple assignment problems efficiently |
| lap_solve_kbest | Find k-best optimal assignments |
| lap_solve_line_metric | Solve 1-D Line Assignment Problem |
| lazy_cost_spec_calipers | Calipers of a lazy cost spec, keyed by variable name |
| lazy_cost_spec_inv_cov | Precompute the Mahalanobis inverse covariance matrix for a... |
| lazy_cost_spec_mode | The memory mode a lazy cost specification was built for |
| lazy_pair_distances | Compute paired (not cross) distances for specific matched... |
| long_to_cost_matrix | Build a cost matrix from source / target / cost columns |
| mark_forbidden_pairs | Mark forbidden pairs |
| mask_forbidden | Apply the 'forbidden' sentinel to a cost matrix |
| match_blocks_parallel | Match blocks in parallel |
| match_couples | Match two datasets into couples |
| match_couples_blocked | Match with blocking (multiple problems) |
| match_couples_from_distance | Match from Precomputed Distance Object |
| match_couples_single | Match without blocking (single problem) |
| match_data | Extract Analysis-Ready Data from Matching Results |
| matchmaker | Create blocks for stratified matching |
| match_path | Match across a range of one design choice |
| new_lazy_cost_spec | Construct a lazy cost specification |
| parallel_lapply | Parallel lapply using future |
| pixel_morph | Pixel-level image morphing (final frame only) |
| pixel_morph_animate | Pixel-level image morphing (animation) |
| plot.balance_diagnostics | Plot method for balance diagnostics |
| plot.matching_result | Plot method for matching results |
| plot.sensitivity_analysis | Plot method for sensitivity analysis (base graphics) |
| preprocess_matching_vars | Preprocess matching variables with automatic checks and... |
| print.balance_diagnostics | Print Method for Balance Diagnostics |
| print.cem_result | Print Method for CEM Results |
| print.couplr_flow_problem | Print Method for Flow Problems |
| print.couplr_path | Print a design path |
| print.distance_object | Print Method for Distance Objects |
| print.full_matching_result | Print Method for Full Matching Results |
| print.lap_solve_batch_result | Print method for batch assignment results |
| print.lap_solve_kbest_result | Print method for k-best assignment results |
| print.lap_solve_result | Print method for assignment results |
| print.matching_result | Print method for matching results |
| print.matchmaker_result | Print method for matchmaker results |
| print.preprocessing_result | Print method for preprocessing result |
| print.sensitivity_analysis | Print method for sensitivity analysis |
| print.subclass_result | Print Method for Subclassification Results |
| print.variable_health | Print method for variable health |
| ps_match | Propensity Score Matching |
| reexports | Objects exported from other packages |
| resolve_memory_mode | Resolve a requested memory_mode to a concrete decision |
| restore_parallel | Restore original parallel plan |
| sensitivity_analysis | Rosenbaum Sensitivity Analysis |
| setup_parallel | Setup parallel processing with future |
| sinkhorn | 'Sinkhorn-Knopp' optimal transport solver |
| sinkhorn_to_assignment | Round 'Sinkhorn' transport plan to hard assignment |
| solver_status_values | Solver status values |
| standardized_difference | Calculate Standardized Difference |
| subclass_match | Subclassification on Propensity Score |
| success_good_balance | Perfect balance success message |
| suggest_scaling | Suggest scaling method based on variable characteristics |
| summarize_blocks | Summarize block structure |
| summary.balance_diagnostics | Summary method for balance diagnostics |
| summary.distance_object | Summary Method for Distance Objects |
| summary.lap_solve_kbest_result | Get summary of k-best results |
| summary.matching_result | Summary method for matching results |
| summary.sensitivity_analysis | Summary method for sensitivity analysis |
| transpose_lazy_cost_spec | Swap left/right in a lazy cost spec |
| update_constraints | Update Constraints on Distance Object |
| use_emoji | Check if emoji should be used |
| validate_calipers | Validate calipers parameter |
| validate_cost_data | Validate and prepare cost data |
| validate_matching_inputs | Validate matching inputs |
| validate_weights | Validate weights parameter |
| verify_assignment | Verify that an assignment is optimal |
| verify_flow | Verify that a flow is optimal |
| vm_stat_available_mb | Available megabytes implied by a block of 'vm_stat' output |
| vm_stat_page_size | Page size behind a block of 'vm_stat' output |
| warn_constant_distance | All distances identical warning |
| warn_constant_var | Constant variable warning |
| warn_extreme_costs | Extreme cost ratio warning |
| warn_many_forbidden | Many forbidden pairs warning |
| warn_many_zeros | Too many zeros warning |
| warn_parallel_unavailable | Parallel package missing warning (reuse from... |
| warn_poor_quality | High distance matches warning |
