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joinet  

Penalised Multivariate Regression ('Multi-Target Learning')
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("joinet", "1.0.0")



Attach the package and use:
library("joinet")
Maintained by
Armin Rauschenberger
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-08-03
Latest Update: 2024-09-27
Description:
Implements high-dimensional multivariate regression by stacked generalisation (Rauschenberger 2021 ). For positively correlated outcomes, a single multivariate regression is typically more predictive than multiple univariate regressions. Includes functions for model fitting, extracting coefficients, outcome prediction, and performance measurement. If required, install MRCE or remMap from GitHub (, ).
How to cite:
Armin Rauschenberger (2019). joinet: Penalised Multivariate Regression ('Multi-Target Learning'). R package version 1.0.0, https://cran.r-project.org/web/packages/joinet. Accessed 28 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:50), 0.0.1 (2019-08-03 08:50), 0.0.2 (2019-08-08 18:40), 0.0.3 (2019-11-13 16:40), 0.0.5 (2020-10-03 07:50), 0.0.6 (2020-11-23 11:50), 0.0.7 (2021-03-09 10:00), 0.0.8 (2021-07-16 09:30), 0.0.9 (2021-07-16 14:20), 0.0.10 (2021-08-09 09:40)
Other packages that cited joinet R package
View joinet citation profile
Other R packages that joinet depends, imports, suggests or enhances
Complete documentation for joinet
Functions, R codes and Examples using the joinet R package
Some associated functions: coef.joinet . cv.joinet . joinet-package . joinet . predict.joinet . weights.joinet . 
Some associated R codes: functions.R . pkgname.R .  Full joinet package functions and examples
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