Package: rpms
Type: Package
Title: Recursive Partitioning for Modeling Survey Data
Version: 0.4.0
Date: 2019-05-30
Authors@R: person("Daniell", "Toth", email="danielltoth@yahoo.com",
    role=c("aut", "cre"))
Maintainer: Daniell Toth <danielltoth@yahoo.com>
Description: Functions to allow users to build and analyze design consistent 
    tree and random forest models using survey data from a complex sample 
    design.  The algorithm can fit a linear model to survey data in each 
    node obtained by recursively partitioning the data.  The splitting 
    variables and selected splits are obtained using a randomized permutation 
    test procedure which adjusted for complex sample design features used to 
    obtain the data. Likewise the model fitting algorithm produces 
    design-consistent coefficients to any specified least squares linear model 
    between the dependent and independent variables used in the end nodes.
    The main functions return the resulting binary tree or random forest as 
    an object of "rpms" or "rpms_forest" type. The package also provides a number 
    of functions and methods available for use with these object types.
License: CC0
Depends: R (>= 2.10)
Imports: Rcpp (>= 0.12.3)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: yes
LazyData: true
Packaged: 2019-05-30 17:01:32 UTC; goddess
Author: Daniell Toth [aut, cre]
Repository: CRAN
Date/Publication: 2019-05-30 22:10:47 UTC
Built: R 4.0.2; x86_64-apple-darwin17.0; 2020-07-15 15:58:56 UTC; unix
Archs: rpms.so.dSYM
