HAMMER: High-Dimensional Factor-Analytic Representation Modeling and
Metrics
The goal of 'HAMMER' is to provide factor analytic representation
learningand 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.
| Version: |
1.0 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
stats, RSpectra |
| Published: |
2026-06-08 |
| DOI: |
10.32614/CRAN.package.HAMMER (may not be active yet) |
| 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:
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