lazymatrix 0.1.0

Initial CRAN submission.

New Features

• Introduced lazy evaluation framework for working with normalized sparse matrices
• Represent large sparse matrices symbolically with the S4 object LazyMatrix
• Fundamental matrix operations like matrix-vector multiplication and transpose matrix-vector multiplication supported for the LazyMatrix object
• Added support for subsetting methods, mirroring matrix objects from base R and Matrix. The symbolic equivalent of column vectors is called LazyColumn
• Implemented specific statistical algorithms, LSQR, truncated partial SVD, for showcasing how lazymatrix can be implemented
• Optimized internal C++ loops for sparse matrix operations using RcppArmadillo.

Improvements

• Optimized matrix multiplication for lazy objects to avoid materialization
• Added vignette demonstrating typical workflow with large sparse datasets

Bug Fixes

• No known bugs fixed in initial release

Documentation

• Added comprehensive roxygen2 documentation for all exported functions
• Included example code in each function’s documentation
• Wrote getting started vignette covering installation and basic usage

Internal Changes

• Utilized Matrix package for underlying sparse matrix representation
• Implemented partial SVD using irlba