gbm3/DESCRIPTION at master · gbm-developers/gbm3 · GitHub

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Package: gbm3
Version: 3.0.3
Date: 2026-07-15
Title: Generalized Boosted Regression Models
Authors@R: c(
    person("James", "Hickey",
           email="james.hickey@cantab.net",
           role="aut"),
    person("Paul", "Metcalfe",
           email="paul.metcalfe@gmail.com",
           role=c("aut")),
    person("Greg", "Ridgeway",
           email="gridge@upenn.edu",
           role=c("aut", "cre")),
    person("Stefan", "Schroedl",
           email="schroedl@a9.com",
           role="aut"),
    person("Harry", "Southworth",
           email="harry.southworth@gmail.com",
           role="aut"),
    person("Terry", "Therneau",
           email="therneau.terry@mayo.edu",
           role="aut")
    )
Depends:
    R (>= 3.5.0)
Imports:
    survival,
    lattice,
    splines,
    Rcpp (>= 1.0.0)
Suggests:
    testthat (>= 3.1.0),
    knitr,
    rmarkdown,
    MASS
VignetteBuilder: knitr
Description: Extensions to Freund and Schapire's AdaBoost algorithm, Y. Freund
    and R. Schapire (1997) <doi:10.1006/jcss.1997.1504> and Friedman's gradient
    boosting machine, J.H. Friedman (2001) <doi:10.1214/aos/1013203451>.
    Includes regression methods for least squares, absolute loss,
    t-distribution loss, quantile regression, logistic, Poisson,
    Cox proportional hazards partial likelihood, AdaBoost
    exponential loss, Huberized hinge loss,
    and Learning to Rank measures (LambdaMART).
License: GPL (>= 2)
URL: https://gbm-developers.github.io/gbm3/,
    https://github.com/gbm-developers/gbm3
Encoding: UTF-8
LinkingTo: Rcpp
RoxygenNote: 8.0.0