addBalance              Add fine balance edges
addExclusion            Add exclusion edges
balanceCosts            Create a skeleton representation of the balance
                        edge costs
build.dist.struct       An internal helper function that generates the
                        data abstraction for the edge weights of the
                        main network structure.
build.dist.struct_user
                        An internal helper function that generates the
                        data abstraction for the edge weights of the
                        main network structure using the distance
                        matrix passed by the user.
callrelax               Call relax on the network
check_representative    Check the representativeness of matched treated
                        units
combine_dist            An internal helper function that combines two
                        distance object
combine_match_result    Combine two matching result
compare_matching        Generate covariate balance in different matches
compare_tables          Summarize covariate balance table
convert_index           An internal helper function that translates the
                        matching index in the sorted data frame to the
                        original dataframe's row index
convert_names           Internal helper function that converts axis
                        name to internal variable name
costSkeleton            Create cost skeleton
data_precheck           Data precheck: Handle missing data(mean
                        imputation) and remove redundant columns; it
                        also adds an NA column for indicating whether
                        it's missing
descr.stats_general     Generate summary statistics for matches
dist_bal_match          Optimal tradeoffs among distance, exclusion and
                        marginal imbalance
distanceFunctionHelper
                        Helper function that change input distance
                        matrix
dummy                   This is a modified version of the function
                        "dummy" from the R package dummies. Original
                        code Copyright (c) 2011 Decision Patterns.
edgelist2ISM            Change the edgelist to the infinity sparse
                        matrix
excludeCosts            Create a skeleton representation of the
                        exclusion edge costs
extractEdges            Extract edges from the network
extractSupply           Extract the supply nodes from the net
filter_match_result     Filter match result
flattenSkeleton         Turns a skeleton representation of edge costs
                        in a network
generateRhoObj          Penalty and objective values summary
generate_rhos           Generate rho pairs
getExactOn              Generate a factor for exact matching.
getPropensityScore      Fit propensity scores using logistic
                        regression.
get_balance_table       Generate balance table
get_five_index          An internal helper function that gives the
                        index of matching with a wide range of number
                        of treated units left unmatched
get_pairdist_balance_graph
                        Total variation imbalance vs. marginal
                        imbalance
get_pairdist_graph      Distance vs. exclusion
get_rho_obj             Penalty and objective values summary
get_tv_graph            Marginal imbalance vs. exclusion
get_unmatched           Get unmatched percentage
makeInfinitySparseMatrix
                        Internal helper to build infinity sparse matrix
makeSparse              Helper function to mask edges
matched_data            Get matched dataframe
matched_index           An internal helper function that translate the
                        matching index in the sorted data frame to the
                        original dataframe's row index
matrix2cost             change the distance matrix to cost
matrix2edgelist         Helper function to convert matrix to list
meldMask                Helper function to combine two sparse distances
netFlowMatch            Create network flow structure
obj.to.match            An internal helper function that transforms the
                        output from the RELAX algorithm to a data
                        structure that is more interpretable for the
                        output of the main matching function
pairCosts               Create a skeleton representation of the edge
                        costs
rho_proposition         Generate penalty coefficient pairs
solveP                  Solve the network flow problem - basic version
solveP1                 Solve the network flow problem - twoDistMatch
summary.multiObjMatch   Generate numerical summary
two_dist_match          Optimal tradeoffs among two distances and
                        exclusion
visualize               Visualize tradeoffs
