Provides a framework for lazy computation on large sparse matrices. Enables lazy evaluation of normalized data matrices, preserving sparsity throughout operations without materializing dense intermediate objects. Implements statistical algorithms including LSQR for sparse least squares as described in Paige and Saunders (1982) <doi:10.1145/355984.355989> and partial singular value decomposition via the augmented implicitly restarted Lanczos bidiagonalization algorithm of Baglama and Reichel (2005) <doi:10.1137/04060593X>.
| Version: | 0.1.0 |
| Imports: | Matrix, methods, stats, irlba, Rcpp |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | bench, dplyr, ggplot2, knitr, rmarkdown, scales, testthat (≥ 3.0.0), tidyr |
| Published: | 2026-07-14 |
| DOI: | 10.32614/CRAN.package.lazymatrix (may not be active yet) |
| Author: | Viktor Segersall [aut, cre, cph] |
| Maintainer: | Viktor Segersall <viktor.segersall at proton.me> |
| License: | GPL (≥ 3) |
| URL: | https://vsegersall.github.io/lazymatrix/ |
| NeedsCompilation: | yes |
| Materials: | README, NEWS |
| CRAN checks: | lazymatrix results |
| Reference manual: | lazymatrix.html , lazymatrix.pdf |
| Vignettes: |
Getting started with LazyMatrix (source, R code) performance (source, R code) Use Cases for LazyMatrix: Statistical Algorithms (source, R code) |
| Package source: | lazymatrix_0.1.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available |
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