Package: MultiwayRegression 1.2

Eric F. Lock

MultiwayRegression: Perform Tensor-on-Tensor Regression

Functions to predict one multi-way array (i.e., a tensor) from another multi-way array, using a low-rank CANDECOMP/PARAFAC (CP) factorization and a ridge (L_2) penalty [Lock, EF (2018) <doi:10.1080/10618600.2017.1401544>]. Also includes functions to sample from the Bayesian posterior of a tensor-on-tensor model.

Authors:Eric F. Lock

MultiwayRegression_1.2.tar.gz
MultiwayRegression_1.2.tar.gz(r-4.5-noble)MultiwayRegression_1.2.tar.gz(r-4.4-noble)
MultiwayRegression_1.2.tgz(r-4.4-emscripten)MultiwayRegression_1.2.tgz(r-4.3-emscripten)
MultiwayRegression.pdf |MultiwayRegression.html
MultiwayRegression/json (API)

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

Peer review:

Datasets:
  • X - Simulated multi-way data for prediction
  • Y - Simulated multi-way data for prediction

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.48 score 1 packages 7 scripts 124 downloads 3 exports 1 dependencies

Last updated 5 years agofrom:60ff7e7928. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 16 2024
R-4.5-linuxOKOct 16 2024

Exports:ctprodrrrrrrBayes

Dependencies:MASS