R Observatory: Metrics for sparseSEM version 4.1

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

sparseSEM

4.1Package record

Elastic Net Penalized Maximum Likelihood for Structural Equation Models with Network GPT Framework

0packages depend

6.2Kdownloads / year

–test coverage

13/13flavors OK

Overview

About

Maintained by Anhui HuangCRAN page ↗

Provides elastic net penalized maximum likelihood estimator for structural equation models (SEM). The package implements `lasso` and `elastic net` (l1/l2) penalized SEM and estimates the model parameters with an efficient block coordinate ascent algorithm that maximizes the penalized likelihood of the SEM. Hyperparameters are inferred from cross-validation (CV). A Stability Selection (STS) function is also available to provide accurate causal effect selection. The software achieves high accuracy performance through a `Network Generative Pre-trained Transformer` (Network GPT) Framework with two steps: 1) pre-trains the model to generate a complete (fully connected) graph; and 2) uses the complete graph as the initial state to fit the `elastic net` penalized SEM.

Install

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

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

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

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-sparsesem

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

# 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-sparseSEM

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-sparseSEM

RPMs auto-built from CRAN on openSUSE OBS (Tumbleweed). We list this channel from recorded autoCRAN download activity rather than from a live index of the repository, so treat it as last known rather than guaranteed.

Health

CRAN checks

13OK

CRAN check page ↗

Slowest check: 4.4 min · r-release-macos-x86_64

Status changes

OK13 OK2026-08-04
NOTE12 OK, 1 NOTE2026-08-01
OK14 OK2026-03-10

Advisories

none known

How this is measured·How advisories are found

Documentation

In release 4.1

READMEYes · 315 wordsVignettesYes · 2 · dynamicNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION

Help pages: 13 (1 internal)includes a package overview page
Examples that run: 100%12 run in a plain check
Exported functions with examples: 100%
Documented parameters: not tracked
Return-value docs: not tracked
Help pages citing references: 92%

Vignettes (2)

How these are measured

Downloads

6.2K

CRAN downloads in the past year

Rank #9,056 · ~17/day · ~515/mo

Releases R versions

Daily download trend is not available in this view yet.

33630 days

1.1K90 days

6.2K1 year

Compare downloads with other packages →

Also on350 r2u7 autocran128 c2d4u

How downloads are counted

Dependencies

Declared dependencies

2 external dependencies (excludes base and recommended)

Installing sparseSEM adds no packages beyond those that come with R.

Depends (1)

R >= 3.5.0

Imports (1)

parallel

LinkingTo (0)

none

Suggests (2)

knitr plot.matrix

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

0direct

0indirect

Nothing depends on this yet.

How these are counted

Code & Tests

Datasets

People & History

People (1)

Anhui Huang

Author, Contributor, Maintainer since 2.3 (2013)

Listed in earlier versions (1)

Xiaodong Cai

no longer listed · 2.3

Releases (7)

Pick two releases to compare their code metrics.

R
R 4.6.0 released · 2026-04-24
R
R 4.5.0 released · 2025-04-11
4.1Latest
record
2024-10-27 · current release · diff ↗
R
R 4.4.0 released · 2024-04-24
4.0
record
2023-08-09 · diff ↗
3.8-2
record
2023-06-11 · diff ↗
3.8-1
record
2023-05-04 · diff ↗
unarchivedReturned to CRAN
2023-04-21
3.8
record
2023-04-21 · diff ↗
R
R 4.3.0 released · 2023-04-21
archivedRemoved from CRAN
2022-05-07
installation issues were not corrected in time
R
R 4.2.0 released · 2022-04-22
R
R 4.1.0 released · 2021-05-18
R
R 4.0.0 released · 2020-04-24
R
R 3.6.0 released · 2019-04-26
R
R 3.5.0 released · 2018-04-23

Show 6 earlier eventsHide 6 earlier events

R
R 3.4.0 released · 2017-04-21
R
R 3.3.0 released · 2016-05-03
R
R 3.2.0 released · 2015-04-16
2.5
record
2014-09-04 · diff ↗
2.3
record
2014-08-26
R
R 3.1.0 released · 2014-04-10

Package metadata

First published: 2014-08-26
Total releases: 7 / 12 yrs
License: GPL
Minimum R: ≥ 3.5.0
Bundled data: 860 KB / 5 files
Download size: 4.5 MB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("sparseSEM")

Format

Huang, A. (2024). sparseSEM: Elastic Net Penalized Maximum Likelihood for Structural Equation Models with Network GPT Framework (Version 4.1) [Computer software]. https://doi.org/10.32614/CRAN.package.sparseSEM

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 sparseSEM version 4.1 [Data set]. HJJB, LLC. Data release v2026-10-25. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-25, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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