R Observatory: Metrics for SuperGauss version 2.0.4

Balamuta, James Joseph

doi:10.5281/zenodo.21843040

SuperGauss

2.0.4

Superfast Likelihood Inference for Stationary Gaussian Time Series

3packages depend

7.3Kdownloads / year

85.4%test coverage

13/13checks pass

Overview

About

Maintained by Martin LysyFirst published 2017-07-068 releasesCRAN page ↗GitHub ↗

Likelihood evaluations for stationary Gaussian time series are typically obtained via the Durbin-Levinson algorithm, which scales as O(n^2) in the number of time series observations. This package provides a "superfast" O(n log^2 n) algorithm written in C++, crossing over with Durbin-Levinson around n = 300. Efficient implementations of the score and Hessian functions are also provided, leading to superfast versions of inference algorithms such as Newton-Raphson and Hamiltonian Monte Carlo. The C++ code provides a Toeplitz matrix class packaged as a header-only library, to simplify low-level usage in other packages and outside of R.

Install

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

install.packages("SuperGauss", 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("mlysy/SuperGauss")

Development version from mlysy/SuperGauss. 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-supergauss

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-SuperGauss

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-SuperGauss

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

Health

CRAN checks

13OK

Slowest check: 5.9 min · r-oldrel-windows-x86_64

Code health

Yes

Tests · ratio 0.66

85.4%

Coverage · measured lines

95%

Documentation · exports

5

Dependencies · direct

Check history

OK2026-08-05
13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
NOTE2026-08-01
12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
OK2026-04-25
12 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
NOTE2026-04-22
12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
ERROR2026-04-18
11 OK · 2 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE

Show 1 earlier snapshots

NOTE2026-03-10
12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

READMENoVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo

Examples that run: 100%
Documented parameters: 100%
Return-value docs: 67%
References docs: 0%

Downloads

7.3K

CRAN downloads in the past year

Rank #5,736 · ~20/day · ~607/mo

Releases R versions

Daily download trend is not available in this view yet.

28030 days

1.4K90 days

7.3K1 year

Compare downloads with other packages →

Also on454 r2u33 autocran

Repository

GitHub ↗ mlysy/supergauss

2Stars

3Forks

0Open issues

1Open PRs

0Releases

215Commits

2Contributors

215 commits · Last activity 2025-09-09

Stars over time

2021-09-01 · 22026-07-07 · 2

Repository practices

Upstream repositoryBeta

2 development-tooling and community-health practices detected across 2 families in the upstream repository

Checks run against github.com/mlysy/supergauss on 2026-08-23.

Continuous integration (1)

GitHub Actions

Git structural (1)

.gitattributes

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

Dependencies

Declared dependencies

10 external dependencies (excludes base and recommended)

Depends (1)

R >= 3.0.0

Imports (5)

statsmethodsR6 Rcpp fftw

LinkingTo (2)

Rcpp RcppEigen

Suggests (5)

knitr rmarkdown testthat mvtnorm numDeriv

Enhances (0)

none

Dependency license breakdown →

Reverse dependencies

3direct

0indirect

AIUQ LMN fastFGEE

Code & Tests

People & History

People (2)

Maintainer (1)

Martin Lysy

Author, Maintainer

Authors (2)

Martin Lysy

Author, Maintainer

Yun Ling

Author

Package Timeline

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

R
R 4.6.0 released · 2026-04-24
2.0.4Latest
2025-09-10 · current release · diff ↗
R
R 4.5.0 released · 2025-04-11
R
R 4.4.0 released · 2024-04-24
R
R 4.3.0 released · 2023-04-21
R
R 4.2.0 released · 2022-04-22
2.0.3
2022-02-24 · diff ↗
2.0.2
2021-10-19 · diff ↗
R
R 4.1.0 released · 2021-05-18
2.0.1
2020-10-03 · diff ↗
2.0.0
2020-09-21 · diff ↗
R
R 4.0.0 released · 2020-04-24
1.0.2
2020-02-27 · diff ↗
R
R 3.6.0 released · 2019-04-26
1.0.1
2019-03-12 · diff ↗
unarchivedReturned to CRAN
2019-03-12

Show 4 earlier events

archivedRemoved from CRAN
2019-03-11
policy violation Missing autoconf sources
R
R 3.5.0 released · 2018-04-23
1.0
2017-07-06
R
R 3.4.0 released · 2017-04-21

Package metadata

First published: 2017-07-06
Total releases: 8 / 9 yrs
License: GPL-3 OSI
Minimum R: ≥ 3.0.0
Download size: 299 KB
Installed size: not tracked yet
With dependencies: not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("SuperGauss")

Format

Lysy, M., & Ling, Y. (2025). SuperGauss: Superfast Likelihood Inference for Stationary Gaussian Time Series (Version 2.0.4) [Computer software]. https://doi.org/10.32614/CRAN.package.SuperGauss

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

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 SuperGauss version 2.0.4 [Data set]. HJJB, LLC. Data release v2026-08-26. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-26, 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 →