fastadi: Self-Tuning Data Adaptive Matrix Imputation

Implements the AdaptiveImpute matrix completion algorithm of 'Intelligent Initialization and Adaptive Thresholding for Iterative Matrix Completion', <https://amstat.tandfonline.com/doi/abs/10.1080/10618600.2018.1518238>. AdaptiveImpute is useful for embedding sparsely observed matrices, often out performs competing matrix completion algorithms, and self-tunes its hyperparameter, making usage easy.

Version: 0.1.1
Depends: LRMF3, Matrix, R (≥ 3.1)
Imports: ellipsis, glue, logger, methods, Rcpp, RSpectra
LinkingTo: Rcpp, RcppArmadillo
Suggests: invertiforms, covr, knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2022-09-07
Author: Alex Hayes ORCID iD [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://github.com/RoheLab/fastadi
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: fastadi results

Documentation:

Reference manual: fastadi.pdf

Downloads:

Package source: fastadi_0.1.1.tar.gz
Windows binaries: r-devel: fastadi_0.1.1.zip, r-release: fastadi_0.1.1.zip, r-oldrel: fastadi_0.1.1.zip
macOS binaries: r-release (arm64): fastadi_0.1.1.tgz, r-oldrel (arm64): fastadi_0.1.1.tgz, r-release (x86_64): fastadi_0.1.1.tgz
Old sources: fastadi archive

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