Multivariate Elastic Net Regression

Implements high-dimensional multivariate regression by stacked generalisation (Wolpert 1992 ). 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 from GitHub (< https://github.com/cran/MRCE>).


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install.packages("joinet")

0.0.6 by Armin Rauschenberger, 3 months ago


https://github.com/rauschenberger/joinet


Report a bug at https://github.com/rauschenberger/joinet/issues


Browse source code at https://github.com/cran/joinet


Authors: Armin Rauschenberger [aut, cre]


Documentation:   PDF Manual  


GPL-3 license


Imports glmnet, palasso, cornet

Suggests knitr, rmarkdown, testthat, MASS

Enhances mice, earth, spls, MRCE, remMap, MultivariateRandomForest, SiER, mcen, GPM, RMTL, MTPS


See at CRAN