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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.2 |
rolling linux/jammy R-4.5 | MultiwayRegression_1.2.tar.gz |
302.9 KiB |
1.2 |
rolling linux/noble R-4.5 | MultiwayRegression_1.2.tar.gz |
303.0 KiB |
1.2 |
rolling source/ R- | MultiwayRegression_1.2.tar.gz |
268.6 KiB |
1.2 |
latest linux/jammy R-4.5 | MultiwayRegression_1.2.tar.gz |
302.9 KiB |
1.2 |
latest linux/noble R-4.5 | MultiwayRegression_1.2.tar.gz |
303.0 KiB |
1.2 |
latest source/ R- | MultiwayRegression_1.2.tar.gz |
268.6 KiB |
1.2 |
2026-04-26 source/ R- | MultiwayRegression_1.2.tar.gz |
268.6 KiB |
1.2 |
2026-04-23 source/ R- | MultiwayRegression_1.2.tar.gz |
268.6 KiB |
1.2 |
2026-04-09 windows/windows R-4.5 | MultiwayRegression_1.2.zip |
306.6 KiB |
1.2 |
2025-04-20 source/ R- | MultiwayRegression_1.2.tar.gz |
268.6 KiB |