HAMMER: High-Dimensional Factor-Analytic Representation Modeling and Metrics
The goal of 'HAMMER' is to provide factor analytic representation learning and associated determinacy metrics for very-high-dimensional data. It projects high-dimensional data onto low-dimensional generative latent sources and assesses the uncertainty in the projection. The projection is distribution-free, scale-equivariant, and efficient. For details, see Peeters (2026) <doi:10.48550/arXiv.2606.28854>.
| Version: | 1.1 |
| Depends: | R (≥ 3.5.0) |
| Imports: | stats, RSpectra |
| Published: | 2026-07-01 |
| DOI: | 10.32614/CRAN.package.HAMMER |
| Author: | Carel F.W. Peeters
 [aut, cre,
cph] |
| Maintainer: | Carel F.W. Peeters <carel.peeters at wur.nl> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | HAMMER results |
Documentation:
| Reference manual: | HAMMER.html , HAMMER.pdf |
Downloads:
| Package source: | HAMMER_1.1.tar.gz |
| Windows binaries: | r-devel: HAMMER_1.0.zip, r-release: HAMMER_1.0.zip, r-oldrel: HAMMER_1.0.zip |
| macOS binaries: | r-release (arm64): HAMMER_1.0.tgz, r-oldrel (arm64): HAMMER_1.0.tgz, r-release (x86_64): HAMMER_1.0.tgz, r-oldrel (x86_64): HAMMER_1.0.tgz |
| Old sources: | HAMMER archive |
Linking:
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