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personalized2part
View on CRAN: Click
here
Download and install personalized2part package within the R console
Install from CRAN:
install.packages("personalized2part")
Install from Github:
library("remotes")
install_github("cran/personalized2part")
Install by package version:
library("remotes")
install_version("personalized2part", "0.0.1")
Attach the package and use:
library("personalized2part")
Maintained by
Jared Huling
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-09-10
Latest Update: 2020-09-10
Description:
Implements the methodology of Huling, Smith, and
Chen (2020) , which allows for subgroup identification
for semi-continuous outcomes by estimating individualized treatment rules. It uses a two-part
modeling framework to handle semi-continuous data by separately modeling the positive part
of the outcome and an indicator of whether each outcome is positive, but still results in a
single treatment rule. High dimensional data is handled with a cooperative lasso penalty,
which encourages the coefficients in the two models to have the same sign.
How to cite:
Jared Huling (2020). personalized2part: Two-Part Estimation of Treatment Rules for Semi-Continuous Data. R package version 0.0.1, https://cran.r-project.org/web/packages/personalized2part
Previous versions and publish date:
No previous versions
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Other R packages that personalized2part depends,
imports, suggests or enhances
Functions, R codes and Examples using
the personalized2part R package
Some associated functions: HDtweedie_kfold_aug . cv.hd2part . fit_subgroup_2part . hd2part . hdgamma . plot . predict.cv.hd2part . predict.hd2part . sim_semicontinuous_data .
Some associated R codes: RcppExports.R . augmentation_functions.R . cv_two_part.R . data_prep_utils.R . fit_subgroup_two_part.R . fit_two_part.R . plot_hd2part.R . predict_two_part.R . simulate_data.R . utils.R . zzz.R . Full personalized2part package functions and examples
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