DESCRIPTION

Package: propensityml
Title: Propensity score weighting using machine learning methods
Version: 0.0.0.9000
Authors@R: 
    person(given = "Young Geun",
           family = "Kim",
           role = c("aut", "cre"),
           email = "dudrmshub@gmail.com")
Maintainer: Young-geun Kim <dudrms33@g.skku.edu>
Description: Implement machine learning models to improve propensity score weight,
    especially tree models, e.g.
    CART, pruned CART, random forests, etc.
License: MIT + file LICENSE
URL: https://github.com/ygeunkim
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.1.1
Imports: 
    stats,
    magrittr,
    data.table,
    Matrix,
    tibble,
    dplyr,
    randomForest,
    rpart,
    e1071,
    stringr,
    mvtnorm,
    methods,
    rlang,
    ggplot2,
    foreach,
    parallel
Depends: 
    R (>= 2.10)
Suggests: 
    testthat,
    covr