rsparse

0.5.3

Statistical Learning on Sparse Matrices

3packages depend

351.7Kdownloads / year

72.1%test coverage

11/13checks pass

Overview

About

Maintained by Dmitriy SelivanovFirst published 2019-04-1210 releasesCRAN page ↗GitHub ↗

Implements many algorithms for statistical learning on sparse matrices - matrix factorizations, matrix completion, elastic net regressions, factorization machines. Also 'rsparse' enhances 'Matrix' package by providing methods for multithreaded <sparse, dense> matrix products and native slicing of the sparse matrices in Compressed Sparse Row (CSR) format. List of the algorithms for regression problems: 1) Elastic Net regression via Follow The Proximally-Regularized Leader (FTRL) Stochastic Gradient Descent (SGD), as per McMahan et al(, doi:10.1145/2487575.2488200) 2) Factorization Machines via SGD, as per Rendle (2010, doi:10.1109/ICDM.2010.127) List of algorithms for matrix factorization and matrix completion: 1) Weighted Regularized Matrix Factorization (WRMF) via Alternating Least Squares (ALS) - paper by Hu, Koren, Volinsky (2008, doi:10.1109/ICDM.2008.22) 2) Maximum-Margin Matrix Factorization via ALS, paper by Rennie, Srebro (2005, doi:10.1145/1102351.1102441) 3) Fast Truncated Singular Value Decomposition (SVD), Soft-Thresholded SVD, Soft-Impute matrix completion via ALS - paper by Hastie, Mazumder et al. (2014, doi:10.48550/arXiv.1410.2596) 4) Linear-Flow matrix factorization, from 'Practical linear models for large-scale one-class collaborative filtering' by Sedhain, Bui, Kawale et al (2016, ISBN:978-1-57735-770-4) 5) GlobalVectors (GloVe) matrix factorization via SGD, paper by Pennington, Socher, Manning (2014, https://aclanthology.org/D14-1162/) Package is reasonably fast and memory efficient - it allows to work with large datasets - millions of rows and millions of columns. This is particularly useful for practitioners working on recommender systems.

Install

R (CRAN)pak (dev)Ubuntu (r2u)Fedora (COPR)openSUSE (OBS)

install.packages("rsparse", repos = "https://cloud.r-project.org/")

Installs the current CRAN release. Prebuilt binaries on Windows and macOS.

if (!requireNamespace("pak", quietly = TRUE))
  install.packages("pak", repos = "https://cloud.r-project.org/")
pak::pak("dselivanov/rsparse")

Development version from dselivanov/rsparse. Installs pak first if it is not already available.

Release

# enable cranapt (r2u) if it is not already set up, then install
grep -rqs r2u.stat.illinois.edu /etc/apt/sources.list /etc/apt/sources.list.d/ \
  || curl -fsSL https://raw.githubusercontent.com/eddelbuettel/r2u/master/inst/scripts/add_cranapt_noble.sh | sudo bash
sudo apt install -y r-cran-rsparse

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled.

bspm (used by r2u) also needs make: sudo apt install make

# enable the iucar/cran COPR if it is not already present, then install
ls /etc/yum.repos.d/*iucar*cran*.repo >/dev/null 2>&1 \
  || sudo dnf copr enable -y iucar/cran
sudo dnf install -y R-CRAN-rsparse

RPMs from the iucar/cran COPR, rebuilt from CRAN.

For install.packages() integration in R, also: sudo dnf install R-CoprManager

# add the autoCRAN OBS repo (Tumbleweed) if it is missing, then install
zypper -q lr | grep -qi autoCRAN \
  || sudo zypper addrepo https://download.opensuse.org/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Tumbleweed/devel:languages:R:autoCRAN.repo
sudo zypper install -y R-rsparse

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed).

Health

CRAN checks

2NOTE11OK

Failing flavors

NOTE r-devel-linux-x86_64-fedora-clang
NOTE r-devel-linux-x86_64-fedora-gcc

Slowest check: 7.2 min · r-oldrel-windows-x86_64

Code health

Yes

Tests · ratio 0.13

72.1%

Coverage · measured lines

100%

Documentation · exports

Dependencies · direct

Check history

NOTE2026-04-22
10 OK · 4 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
ERROR2026-04-18
9 OK · 4 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
NOTE2026-03-10
10 OK · 4 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

READMEYes · 828 wordsVignettesNopkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo

Examples that run: 100%
Documented parameters: 100%
Return-value docs: 10%
References docs: 31%

Downloads

351.7K

CRAN downloads in the past year

Rank #1,623 · ~964/day · ~29.3K/mo

Releases R versions

Daily download trend is not available in this view yet.

3.8K30 days

17.3K90 days

351.7K1 year

Compare downloads with other packages →

Also on695 r2u35 autocran4.3K conda_forge129 c2d4u

Repository

GitHub ↗ dselivanov/rsparse

180Stars

31Forks

7Open issues

3Open PRs

0Releases

350Commits

6Contributors

collaborative-filteringrecommender-systemrmatrix-factorizationmatrix-completionfactorization-machinessvdsparse-matrices

350 commits · Last activity 2026-06-30 · 0% stars, 30d

Stars over time

2025-07-13 · 1772026-07-07 · 180

Repository practices

Upstream repositoryBeta

4 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/dselivanov/rsparse on 2026-07-19.

Continuous integration (1)

GitHub Actions

Reproducibility and dev environment (1)

Makefile

CRAN release process (1)

cran-comments.md

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies

10 external dependencies (excludes base and recommended)

Depends (3)

R >= 3.6.0methodsMatrix

Imports (6)

MatrixExtra Rcpp data.table (>= 1.10.0)float RhpcBLASctl lgr

LinkingTo (2)

Rcpp RcppArmadillo

Suggests (2)

testthat covr

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

3direct

24indirect

text2vec LSX PsychWordVec

Code & Tests

Code Composition

R 3,025 (48%)C++ 1,821 (29%)Rd 1,410 (22%)C 31 (0%)

Code characteristics

Object systems

R69

Cyclomatic complexity: 1.0 median / 22 max
Test cases: 15 / 0.13 per code line

Test coverage

Line coverage

72%

Expression

72.7%

Tests / Examples

72.1% / 48% ex

Functions

158 5 exported

Complexity

2 avg / 22 max

Call network

158 nodes / 87 edges

Call graph

Open call graph →

Loading call graph…

Lowest coverage

158 functions

Function	Cyclo	Coverage
detect_number_omp_threads exp	1	0%
.onLoad	2	0%
install_name_tool_change_float	4	0%
make_csr_identity_matrix	1	0%
predictions_format_error	1	0%
solver_explicit	3	0%

People & History

People (4)

Maintainer (1)

Dmitriy Selivanov

Author, Maintainer, Copyright holder

Authors (1)

Dmitriy Selivanov

Author, Maintainer, Copyright holder

Contributors (3)

Wei-Chen Chen

Contributor

David Cortes

Contributor · added in 0.5.0

Drew Schmidt

Contributor

Dmitriy Selivanov

Author, Maintainer, Copyright holder

Package Timeline

10 releases. Pick two to compare their code metrics. R releases are shown for context.

R
R 4.6.0 released · 2026-04-24
R
R 4.5.0 released · 2025-04-11
0.5.3Latest
2025-02-17 · current release · diff ↗
0.5.2
2024-06-28 · diff ↗
R
R 4.4.0 released · 2024-04-24
R
R 4.3.0 released · 2023-04-21
0.5.1
2022-09-12 · diff ↗
R
R 4.2.0 released · 2022-04-22
0.5.0
2021-11-30 · diff ↗
R
R 4.1.0 released · 2021-05-18
R
R 4.0.0 released · 2020-04-24
0.4.0
2020-04-01 · diff ↗
0.3.3.4
2019-11-14 · diff ↗
0.3.3.3
2019-08-04 · diff ↗
0.3.3.2
2019-07-18 · diff ↗
R
R 3.6.0 released · 2019-04-26

Show 3 earlier events

0.3.3.1
2019-04-14 · diff ↗
0.3.3
2019-04-12
R
R 3.5.0 released · 2018-04-23

Package metadata

First published: 2019-04-12
Total releases: 10 / 7 yrs
License: GPL (>= 2) OSI
Minimum R: ≥ 3.6.0
Bundled data: 98 KB / 1 file
Download size: 210 KB
Installed size: not tracked yet
With dependencies: not tracked yet

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