R Observatory: Metrics for missoNet version 1.5.1

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

missoNet

1.5.1Package record

Joint Sparse Regression & Network Learning with Missing Data

0packages depend

3Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Yixiao ZengCRAN page ↗GitHub ↗Issues ↗

Simultaneously estimates sparse regression coefficients and response network structure in multivariate models with missing data. Unlike traditional approaches requiring imputation, handles missingness natively through unbiased estimating equations (MCAR/MAR compatible). Employs dual L1 regularization with automated selection via cross-validation or information criteria. Includes parallel computation, warm starts, adaptive grids, publication-ready visualizations, and prediction methods. Ideal for genomics, neuroimaging, and multi-trait studies with incomplete high-dimensional outcomes. See Zeng et al. (2025) doi:10.48550/arXiv.2507.05990.

Changes in 1.5.1

> **Major release.** Architecture rebuilt for speed, stability, and cleaner workflows. **Recommend all users upgrade.**

Highlights

**3–5× faster** on typical problems via rewriting core kernels in **RcppArmadillo**.
**Adaptive grid and lambda search** that scales to large problems with fewer evaluations.
**Element-wise precise penalty control** for both coefficients and network edges.

Algorithm & Features

Consistent search strategy in missoNet() and cv.missoNet().
**penalty customization** through beta.pen.factor and theta.pen.factor, enabling exclusion of predictors or structured sparsity patterns.
relax.net option for **de-biased network estimation**: refits the active edge set without L1 penalties to reduce bias in the precision matrix.
Support multiple graphical lasso backends (e.g., glassoFast (default) / glasso) with automatic selection and fallbacks.
Smarter defaults and **data-aware initialization** tuned to dimensionality, missingness, and conditioning.
**Full parallelization** for cross-validation and grid evaluation.

Show all changes in 1.5.1Hide the rest of the changes in 1.5.1

Performance & Robustness

Vectorized algebra and memory reuse; internal benchmarks show **3–5× speedups**
The **warm-start** strategy has been rewritten to enhance stability.
Tighter line search and stopping in FISTA; **fewer oscillations**.
Epsilon‑safe numerics; strict finite‑value checks.

Visualization & UX

**Upgraded** S3 plot() for publication-quality output.
Clearer progress and diagnostics (stages, backend, convergence).

Documentation

**New vignettes: introduction, advanced features, case studies**.
Cross-references and examples aligned across missoNet() and cv.missoNet(); arguments and return values documented consistently.

Bug Fixes

Fixed Inf propagation in preprocessing.
Fixed cross-package reference linking.
Removed unused external data to reduce package size.
Miscellaneous bugs.

> **Compatibility:** Minor API changes; refined defaults. See ?missoNet, ?cv.missoNet.

From NEWS.md in the release

Install

R (CRAN)pak (dev)Ubuntu (r2u)

install.packages("missoNet", 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("yixiao-zeng/missoNet")

Development version from yixiao-zeng/missoNet. 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-missonet

Fast Ubuntu binaries via r2u (no compilation). The cranapt setup runs once and is skipped when it is already enabled. We list this channel from recorded r2u download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

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

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 6.9 min · r-oldrel-windows-x86_64

Status changes

OK13 OK2026-08-05
NOTE12 OK, 1 NOTE2026-08-01
OK13 OK2026-06-08
WARNING12 OK, 1 WARNING2026-06-07
OK12 OK2026-04-25

Show 3 earlier changesHide 3 earlier changes

NOTE12 OK, 2 NOTE2026-04-22
ERROR11 OK, 2 NOTE, 1 ERROR2026-04-18
NOTE12 OK, 2 NOTE2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 1.5.1

READMEYes · 358 wordsVignettesYes · 3 · dynamicNEWSYes · 100% structured · mentions 1.5.1Citation fileNoWebsitenot declared in DESCRIPTION

Help pages: 6includes a package overview page
Examples that run: 100%6 run in a plain check
Exported functions with examples: 100%
Documented parameters: 76%
Return-value docs: 100%
Help pages citing references: 33%

Vignettes (3)

How these are measured

Downloads

3K

CRAN downloads in the past year

Rank #11,322 · ~8/day · ~249/mo

Releases R versions

Daily download trend is not available in this view yet.

36530 days

94490 days

3K1 year

Compare downloads with other packages →

Also on352 r2u

How downloads are counted

Repository

yixiao-zeng/missonet ↗Account: yixiao-zeng

2Stars

0Forks

0Open issues

0Open PRs

1Releases

30Commits

3Commit identities

cranmissing-datamulti-task-regressionr-packageconditional-graphical-lasso

License file reads as GPL-2.0 · 30 commits · Last activity 2025-09-02

Responsiveness

not measured

Stars over time

2025-09-02 · 22026-07-07 · 2

How these are measured

PracticesBeta

5 development-tooling and community-health practices detected across 3 families in the upstream repository

Checks run against github.com/yixiao-zeng/missonet on 2026-10-21.

Continuous integration (2)

GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux

CRAN release process (2)

cran-comments.mdCRAN-SUBMISSION

Lint, format, editor (1)

RStudio project

How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies

17 external dependencies (excludes base and recommended)

Installing missoNet adds 10 packages (5 with compiled code, 9.7 MB of source tarballs). Heaviest: circlize 2.4 MB, colorspace 2.0 MB, Rcpp 1.8 MB. 1 more not on CRAN is not measured.

Depends (1)

R >= 3.6.0

Imports (11)

circlize ComplexHeatmap glassoFastgraphicsgridmvtnorm pbapply Rcpp scatterplot3dstatsutils

LinkingTo (2)

Rcpp RcppArmadillo

Suggests (9)

ggplot2 glasso gridExtra igraph knitrparallelRColorBrewer reshape2 rmarkdown

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

People & History

People (2)

Yixiao Zeng

Celia Greenwood

Thesis advisor, Author

Listed in earlier versions (1)

Archer Yang

no longer listed · 1.0.0 to 1.2.0

Releases (4)

Pick two releases to compare their code metrics.

R
R 4.6.0 released · 2026-04-24
1.5.1Latest
record
2025-09-02 · current release · diff ↗
R
R 4.5.0 released · 2025-04-11
R
R 4.4.0 released · 2024-04-24
unarchivedReturned to CRAN
2023-07-19
archivedRemoved from CRAN
2023-07-19
issues were not corrected in time
1.2.0
record
2023-07-19 · diff ↗
1.1.0
record
2023-05-11 · diff ↗
R
R 4.3.0 released · 2023-04-21
1.0.0
record
2022-10-10
R
R 4.2.0 released · 2022-04-22

Package metadata

First published: 2022-10-10
Total releases: 4 / 4 yrs
License: GPL-2 OSI
Minimum R: ≥ 3.6.0
Download size: 811 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("missoNet")

Format

Zeng, Y., & Greenwood, C. (2025). missoNet: Joint Sparse Regression & Network Learning with Missing Data (Version 1.5.1) [Computer software]. https://doi.org/10.32614/CRAN.package.missoNet

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

Format

APA

Balamuta, J. J. (2026). R Observatory: Metrics for missoNet version 1.5.1 [Data set]. HJJB, LLC. Data release v2026-10-23. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-23, which the citation names so these numbers can be found later. More on citing and the projects behind them.

Report a problem with this page →