fastadi: Self-Tuning Data Adaptive Matrix Imputation
Implements the AdaptiveImpute matrix completion
algorithm of 'Intelligent Initialization and Adaptive Thresholding for
Iterative Matrix Completion' <doi:10.1080/10618600.2018.1518238> as
well as the specialized variant of 'Co-Factor Analysis of
Citation Networks' <doi:10.1080/10618600.2024.2394464>.
AdaptiveImpute is useful for embedding sparsely observed matrices,
often out performs competing matrix completion algorithms, and
self-tunes its hyperparameter, making usage easy.
| Version: |
0.1.2 |
| Depends: |
LRMF3, Matrix, R (≥ 3.1) |
| Imports: |
glue, logger, methods, Rcpp, rlang, RSpectra |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
invertiforms, covr, knitr, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2025-05-02 |
| DOI: |
10.32614/CRAN.package.fastadi |
| Author: |
Alex Hayes  [aut,
cre, cph],
Juhee Cho [aut],
Donggyu Kim [aut],
Karl Rohe [aut] |
| Maintainer: |
Alex Hayes <alexpghayes at gmail.com> |
| BugReports: |
https://github.com/RoheLab/fastadi/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://rohelab.github.io/fastadi/,
https://github.com/RoheLab/fastadi |
| NeedsCompilation: |
yes |
| Materials: |
README, NEWS |
| CRAN checks: |
fastadi results |
Documentation:
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