studyStrap
Study Strap and Multi-Study Learning Algorithms
Implements multi-study learning algorithms such as merging, the study-specific ensemble (trained-on-observed-studies ensemble) the study strap, the covariate-matched study strap, covariate-profile similarity weighting, and stacking weights. Embedded within the 'caret' framework, this package allows for a wide range of single-study learners (e.g., neural networks, lasso, random forests). The package offers over 20 default similarity measures and allows for specification of custom similarity measures for covariate-profile similarity weighting and an accept/reject step. This implements methods described in Loewinger, Kishida, Patil, and Parmigiani. (2019) <doi:10.1101/856385>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.0 |
rolling linux/jammy R-4.5 | studyStrap_1.0.0.tar.gz |
92.9 KiB |
1.0.0 |
rolling linux/noble R-4.5 | studyStrap_1.0.0.tar.gz |
92.8 KiB |
1.0.0 |
rolling source/ R- | studyStrap_1.0.0.tar.gz |
35.4 KiB |
1.0.0 |
latest linux/jammy R-4.5 | studyStrap_1.0.0.tar.gz |
92.9 KiB |
1.0.0 |
latest linux/noble R-4.5 | studyStrap_1.0.0.tar.gz |
92.8 KiB |
1.0.0 |
latest source/ R- | studyStrap_1.0.0.tar.gz |
35.4 KiB |
1.0.0 |
2026-04-26 source/ R- | studyStrap_1.0.0.tar.gz |
35.4 KiB |
1.0.0 |
2026-04-23 source/ R- | studyStrap_1.0.0.tar.gz |
35.4 KiB |
1.0.0 |
2026-04-09 windows/windows R-4.5 | studyStrap_1.0.0.zip |
96.0 KiB |
1.0.0 |
2025-04-20 source/ R- | studyStrap_1.0.0.tar.gz |
35.4 KiB |