Implements structural estimators to correct for
    the sample selection bias from observed outcomes in matching
    markets. This includes one-sided matching of agents into groups 
    (Klein, 2015) <https://www.econ.cam.ac.uk/research-files/repec/cam/pdf/cwpe1521.pdf> 
    as well as two-sided matching of students to schools 
    (Aue et al., 2020) <https://ftp.zew.de/pub/zew-docs/dp/dp20032.pdf>.
    The package also contains algorithms to find stable matchings
    in the three most common matching problems: the stable roommates
    problem (Irving, 1985) <doi:10.1016/0196-6774(85)90033-1>, 
    the college admissions problem (Gale and Shapley, 1962) <doi:10.2307/2312726>, 
    and the house allocation problem (Shapley and Scarf, 1974) <doi:10.1016/0304-4068(74)90033-0>.

Computes matching algorithms quickly using Rcpp.
    Implements the Gale-Shapley Algorithm to compute the stable
    matching for two-sided markets, such as the stable marriage
    problem and the college-admissions problem. Implements Irving's
    Algorithm for the stable roommate problem. Implements the top
    trading cycle algorithm for the indivisible goods trading problem.

Selects matched samples of the original treated and
    control groups with similar covariate distributions -- can be
    used to match exactly on covariates, to match on propensity
    scores, or perform a variety of other matching procedures.  The
    package also implements a series of recommendations offered in
    Ho, Imai, King, and Stuart (2007) <DOI:10.1093/pan/mpl013>. (The 
    'gurobi' package, which is not on CRAN, is optional and comes with 
    an installation of the Gurobi Optimizer, available at 
    <https://www.gurobi.com>.)

Core functions as well as diagnostic and calibration tools for combining matching and linear regression for causal inference in observational studies.

Provides flexible dictionary-based
    cleaning that allows users to specify implicit and explicit missing data,
    regular expressions for both data and columns, and global matches, while
    respecting ordering of factors. This package is part of the 'RECON'
    (<https://www.repidemicsconsortium.org/>) toolkit for outbreak analysis.