Marek Gagolewski [aut, cre] (<https://orcid.org/0000-0003-0637-6028>),
    Bartek Tartanus [ctb],
    and other contributors (stringi source code);
    IBM, Unicode, Inc., and other contributors (ICU4C source code);
    Unicode, Inc. (Unicode Character Database)

c(person("Terry", "Therneau", role = "aut",
	            email = "therneau@mayo.edu"),
             person("Beth", "Atkinson", role = c("aut", "cre"),
	            email = "atkinson@mayo.edu"),
             person("Brian", "Ripley", role = "trl",
                    email = "ripley@stats.ox.ac.uk",
		    comment = "producer of the initial R port, maintainer 1999-2017"))

Recursive partitioning for classification, 
  regression and survival trees.  An implementation of most of the 
  functionality of the 1984 book by Breiman, Friedman, Olshen and Stone.

Recursive Partitioning and Regression Trees

R (>= 2.15.0), graphics, stats, grDevices

Terry Therneau [aut],
  Beth Atkinson [aut, cre],
  Brian Ripley [trl] (producer of the initial R port, maintainer
    1999-2017)

Phil Spector, Jerome Friedman, Robert Tibshirani, Thomas Lumley, Shawn Garbett, Jonathan Baron

Two nonparametric methods for multiple regression transform selection are provided.
  The first, Alternative Conditional Expectations (ACE), 
  is an algorithm to find the fixed point of maximal
  correlation, i.e. it finds a set of transformed response variables that maximizes R^2
  using smoothing functions [see Breiman, L., and J.H. Friedman. 1985. "Estimating Optimal Transformations
  for Multiple Regression and Correlation". Journal of the American Statistical Association.
  80:580-598. <doi:10.1080/01621459.1985.10478157>].
  Also included is the Additivity Variance Stabilization (AVAS) method which works better than ACE when
  correlation is low [see Tibshirani, R.. 1986. "Estimating Transformations for Regression via Additivity
  and Variance Stabilization". Journal of the American Statistical Association. 83:394-405. 
  <doi:10.1080/01621459.1988.10478610>]. A good introduction to these two methods is in chapter 16 of
  Frank Harrel's "Regression Modeling Strategies" in the Springer Series in Statistics.