Perform Complex Matrix Operations Symbolically on Sparse Matrices R package lazymatrix version 0.1.0 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>. Software Imports: Matrix, methods, stats, irlba, Rcpp LinkingTo: Rcpp, RcppArmadillo Suggests: bench, dplyr, ggplot2, knitr, rmarkdown, scales, testthat (>= 3.0.0), tidyr Viktor Segersall <viktor.segersall@proton.me> Comprehensive R Archive Network (CRAN) Viktor Segersall [aut, cre, cph] GPL (>= 3) 2026-07-14 application/tgz https://CRAN.R-project.org/package=lazymatrix doi:10.32614/CRAN.package.lazymatrix