Implements an anomaly detection algorithm based on
    mutual reachability minimum spanning trees: 'deadwood' trims
    protruding tree segments and marks small debris as outliers;
    see Gagolewski (2026) <https://deadwood.gagolewski.com/>.
    More precisely, the use of a mutual reachability distance pulls
    peripheral points farther away from each other.  Tree edges
    with weights beyond the detected elbow point are removed.
    All the resulting connected components whose sizes are smaller
    than a given threshold are deemed anomalous.
    The 'Python' version of 'deadwood' is available via 'PyPI'.

Bayesian networks with continuous and/or discrete
        variables can be learned and compared from data. The method is described in Boettcher and Dethlefsen (2003), <doi:10.18637/jss.v008.i20>.

Set of functions for Data Envelopment Analysis, including classical, fuzzy, cross-efficiency, bootstrapping, and Malmquist models. See: Banker, R.; Charnes, A.; Cooper, W.W. (1984). <doi:10.1287/mnsc.30.9.1078>, Charnes, A.; Cooper, W.W.; Rhodes, E. (1978). <doi:10.1016/0377-2217(78)90138-8> and Charnes, A.; Cooper, W.W.; Rhodes, E. (1981). <doi:10.1287/mnsc.27.6.668>.

High-dimensional visualization methods for data envelopment
    analysis (DEA), gathering in one place techniques that have appeared in the
    literature but remained scattered and largely unimplemented: cross-efficiency
    matrix unfolding, the Porembski network with lambda edges,
    principal component analysis biplots, multidimensional-scaling
    colour-plots, self-organizing maps, the Costa bi-dimensional efficient
    frontier, parallel coordinates, radar charts, panel-data trajectory biplots,
    peer and reference networks, and a set of descriptive plots. The package is
    built around a single validated dea_data() object and uses the 'Benchmarking'
    package as its DEA engine. The implemented methods draw on a body of
    literature; representative references include Doyle and Green (1994)
    <doi:10.1057/jors.1994.84>, Porembski, Breitenstein and Alpar (2005)
    <doi:10.1007/s11123-005-1328-5> and Bana e Costa, Soares de Mello and Angulo
    Meza (2016) <doi:10.1016/j.ejor.2016.05.012>.