Optimal Pairing and Matching via Linear Assignment
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Documentation for package ‘couplr’ version 1.2.1
Help Pages
| assignment | Linear assignment solver |
| assignment_duals | Solve assignment problem and return dual variables |
| as_assignment_matrix | Convert assignment result to a binary matrix |
| as_matchit | Convert couplr Result to matchit Object |
| augment | Generic Augment Function |
| augment.matching_result | Augment Matching Results with Original Data (broom-style) |
| autoplot.balance_diagnostics | ggplot2 autoplot for balance diagnostics |
| autoplot.matching_result | ggplot2 autoplot for matching results |
| autoplot.sensitivity_analysis | ggplot2 autoplot for sensitivity analysis |
| bal.tab.cem_result | Balance Table for Matching Results (cobalt integration) |
| bal.tab.full_matching_result | Balance Table for Matching Results (cobalt integration) |
| bal.tab.matching_result | Balance Table for Matching Results (cobalt integration) |
| bal.tab.subclass_result | Balance Table for Matching Results (cobalt integration) |
| balance_diagnostics | Balance Diagnostics for Matched Pairs |
| balance_diagnostics.cem_result | Balance Diagnostics for Matched Pairs |
| balance_diagnostics.full_matching_result | Balance Diagnostics for Matched Pairs |
| balance_diagnostics.matching_result | Balance Diagnostics for Matched Pairs |
| balance_diagnostics.subclass_result | Balance Diagnostics for Matched Pairs |
| balance_table | Create Balance Table |
| bottleneck_assignment | Solve the Bottleneck Assignment Problem |
| cardinality_match | Cardinality Matching |
| cem_match | Coarsened Exact Matching |
| compute_distances | Compute and Cache Distance Matrix for Reuse |
| diagnose_distance_matrix | Diagnose distance matrix and suggest fixes |
| example_costs | Example cost matrices for assignment problems |
| example_df | Example assignment problem data frame |
| full_match | Full Matching |
| get_method_used | Extract method used from assignment result |
| get_total_cost | Extract total cost from assignment result |
| greedy_couples | Fast approximate matching using greedy algorithm |
| hospital_staff | Hospital staff scheduling example dataset |
| 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 |
| join_matched.cem_result | Join Matched Pairs with Original Data |
| join_matched.full_matching_result | Join Matched Pairs with Original Data |
| join_matched.matching_result | Join Matched Pairs with Original Data |
| join_matched.subclass_result | Join Matched Pairs with Original Data |
| 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 |
| matchmaker | Create blocks for stratified matching |
| match_couples | Optimal matching using linear assignment |
| match_data | Extract Analysis-Ready Data from Matching Results |
| match_data.cem_result | Extract Analysis-Ready Data from Matching Results |
| match_data.full_matching_result | Extract Analysis-Ready Data from Matching Results |
| match_data.matching_result | Extract Analysis-Ready Data from Matching Results |
| match_data.subclass_result | Extract Analysis-Ready Data from Matching Results |
| 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 scaling |
| print.balance_diagnostics | Print Method for Balance Diagnostics |
| print.cem_result | Print Method for CEM Results |
| 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 |
| sensitivity_analysis | Rosenbaum Sensitivity Analysis |
| sinkhorn | 'Sinkhorn-Knopp' optimal transport solver |
| sinkhorn_to_assignment | Round 'Sinkhorn' transport plan to hard assignment |
| subclass_match | Subclassification on Propensity Score |
| 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 |
| update_constraints | Update Constraints on Distance Object |