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rpms  

Recursive Partitioning for Modeling Survey Data
View on CRAN: Click here


Download and install rpms package within the R console
Install from CRAN:
install.packages("rpms")

Install from Github:
library("remotes")
install_github("cran/rpms")

Install by package version:
library("remotes")
install_version("rpms", "0.5.1")



Attach the package and use:
library("rpms")
Maintained by
Daniell Toth
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-10-21
Latest Update: 2021-06-25
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 tree model 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 methods modeling a "boosted" tree or forest model and a tree model for zero-inflated data as well as a number of functions and methods available for use with these object types.
How to cite:
Daniell Toth (2016). rpms: Recursive Partitioning for Modeling Survey Data. R package version 0.5.1, https://cran.r-project.org/web/packages/rpms. Accessed 04 Jun. 2026.
Previous versions and publish date:
0.1.0 (2016-10-21 21:56), 0.2.0 (2017-02-04 08:42), 0.2.1 (2017-06-02 17:34), 0.3.0 (2018-05-05 08:22), 0.4.0 (2019-05-31 00:13)
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Complete documentation for rpms
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