Dimension-reduction methods aim at defining a score that maximizes signal diversity. Three approaches, tree weight, maximum entropy weights, and maximum variance weights are provided. These methods are described in He and Fong (2019) <DOI:10.1002/sim.8212>.
https://anaconda.org/r/r-mdw/badges/version.svg
https://anaconda.org/r/r-mdw/badges/latest_release_date.svg
https://anaconda.org/r/r-mdw/badges/latest_release_relative_date.svg
https://anaconda.org/r/r-mdw/badges/platforms.svg
https://anaconda.org/r/r-mdw/badges/license.svg
https://anaconda.org/r/r-mdw/badges/downloads.svg