Other packages > Find by keyword >

ITRLearn  

Statistical Learning for Individualized Treatment Regime
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("ITRLearn", "1.0-1")



Attach the package and use:
library("ITRLearn")
Maintained by
Chengchun Shi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-10-30
Latest Update: 2023-08-19
Description:
Maximin-projection learning (MPL, Shi, et al., 2018) is implemented for recommending a meaningful and reliable individualized treatment regime for future groups of patients based on the observed data from different populations with heterogeneity in individualized decision making. Q-learning and A-learning are implemented for estimating the groupwise contrast function that shares the same marginal treatment effects. The packages contains classical Q-learning and A-learning algorithms for a single stage study as a byproduct. More functions will be added at later versions.
How to cite:
Chengchun Shi (2018). ITRLearn: Statistical Learning for Individualized Treatment Regime. R package version 1.0-1, https://cran.r-project.org/web/packages/ITRLearn. Accessed 03 Feb. 2025.
Previous versions and publish date:
1.0-1 (2018-11-15 06:10), 1.0 (2018-10-30 19:40)
Other packages that cited ITRLearn R package
View ITRLearn citation profile
Other R packages that ITRLearn depends, imports, suggests or enhances
Functions, R codes and Examples using the ITRLearn R package
Some associated functions: ITRLearn-package . MPL.control . MPL . TR . maximin . 
Some associated R codes: MPL.R . MPL.control.R . MPL.fit.R . TR.R . maximin.R .  Full ITRLearn package functions and examples
Downloads during the last 30 days
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

cmce  
Computer Model Calibration for Deterministic and Stochastic Simulators
Implements the Bayesian calibration model described in Pratola and Chkrebtii (2018) ...
Download / Learn more Package Citations See dependency  
SMR  
Externally Studentized Midrange Distribution
Computes the studentized midrange distribution (pdf, cdf and quantile) and generates random numbers. ...
Download / Learn more Package Citations See dependency  
HGMND  
Heterogeneous Graphical Model for Non-Negative Data
Graphical model is an informative and powerful tool to explore the conditional dependence relationsh ...
Download / Learn more Package Citations See dependency  
nextGenShinyApps  
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency  
sgof  
Multiple Hypothesis Testing
Seven different methods for multiple testing problems. The SGoF-type methods (see for example, Carva ...
Download / Learn more Package Citations See dependency  
metaboData  
Example Metabolomics Data Sets
Data sets from a variety of biological sample matrices, analysed using a number of mass spectrometr ...
Download / Learn more Package Citations See dependency  

23,630

R Packages

204,513

Dependencies

64,101

Author Associations

23,581

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA