Package: joinet 1.0.0

joinet: Penalised Multivariate Regression ('Multi-Target Learning')

Implements penalised multivariate regression (i.e., for multiple outcomes and many features) by stacked generalisation (<doi:10.1093/bioinformatics/btab576>). 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. For optional comparisons, install 'remMap' from GitHub (<https://github.com/cran/remMap>).

Authors:Armin Rauschenberger [aut, cre]

joinet_1.0.0.tar.gz
joinet_1.0.0.zip(r-4.5)joinet_1.0.0.zip(r-4.4)joinet_1.0.0.zip(r-4.3)
joinet_1.0.0.tgz(r-4.4-any)joinet_1.0.0.tgz(r-4.3-any)
joinet_1.0.0.tar.gz(r-4.5-noble)joinet_1.0.0.tar.gz(r-4.4-noble)
joinet_1.0.0.tgz(r-4.4-emscripten)joinet_1.0.0.tgz(r-4.3-emscripten)
joinet.pdf |joinet.html
joinet/json (API)
NEWS

# Install 'joinet' in R:
install.packages('joinet', repos = c('https://rauschenberger.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/rauschenberger/joinet/issues

On CRAN:

5.56 score 4 stars 1 packages 8 scripts 622 downloads 2 exports 12 dependencies

Last updated 2 months agofrom:d5f0b58128. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 27 2024
R-4.5-winOKOct 27 2024
R-4.5-linuxOKOct 27 2024
R-4.4-winNOTEOct 27 2024
R-4.4-macNOTEOct 27 2024
R-4.3-winNOTEOct 27 2024
R-4.3-macNOTEOct 27 2024

Exports:cv.joinetjoinet

Dependencies:codetoolscornetforeachglmnetiteratorslatticeMatrixpalassoRcppRcppEigenshapesurvival

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Rendered fromscript.Rmdusingknitr::rmarkdownon Oct 27 2024.

Last update: 2021-07-14
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Multivariate Elastic Net Regression

Rendered fromarticle.Rmdusingknitr::rmarkdownon Oct 27 2024.

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Multivariate Elastic Net Regression

Rendered fromvignette.Rmdusingknitr::rmarkdownon Oct 27 2024.

Last update: 2024-09-27
Started: 2018-06-14