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sjSDM

1.0.7Package record

Scalable Joint Species Distribution Modeling

0packages depend
3.5Kdownloads / year
8.9%test coverage
11/13flavors OK

Overview

About

A scalable and fast method for estimating joint Species Distribution Models (jSDMs) for big community data, including eDNA data. The package estimates a full (i.e. non-latent) jSDM with different response distributions (including the traditional multivariate probit model). The package allows to perform variation partitioning (VP) / ANOVA on the fitted models to separate the contribution of environmental, spatial, and biotic associations. In addition, the total R-squared can be further partitioned per species and site to reveal the internal metacommunity structure, see Leibold et al., doi:10.1111/oik.08618. The internal structure can then be regressed against environmental and spatial distinctiveness, richness, and traits to analyze metacommunity assembly processes. The package includes support for accounting for spatial autocorrelation and the option to fit responses using deep neural networks instead of a standard linear predictor. As described in Pichler & Hartig (2021) doi:10.1111/2041-210X.13687, scalability is achieved by using a Monte Carlo approximation of the joint likelihood implemented via 'PyTorch' and 'reticulate', which can be run on CPUs or GPUs.

Changes in 1.0.7
  • importance function was removed (deprecated)

Bug fixes

  • cv function, use correct indices in parallel block modus #155, thanks to @jannebor
  • remove ggtern dependency

From NEWS.md in the release

Install

Health

CRAN checks
2WARNING11OK
Check messages
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CRAN check page ↗

Slowest check: 14.1 min · r-release-windows-x86_64
Status changes
  • WARNING11 OK, 2 WARNINGNow
  • WARNING12 OK, 1 WARNING2026-09-10
  • OK13 OK2026-08-04
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-05-28
  • ERROR12 OK, 1 ERROR2026-05-20
Show 1 earlier changeHide 1 earlier change
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 1.0.7
READMEYes · 35 wordsVignettesYes · 1 · staticNEWSYes · 100% structured · mentions 1.0.7Citation fileYes · cites a publication
Help pages
59includes a package overview page
Examples that run
0%18 never run
Exported functions with examples
28%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
17%

Downloads

3.5K
CRAN downloads in the past year
Rank #8,965 · ~10/day · ~292/mo
Daily download trend is not available in this view yet.
40530 days
1.1K90 days
3.5K1 year
Compare downloads with other packages →
Also on119 r2u2 autocran49 c2d4u

Repository

79Stars
17Forks
57Open issues
0Open PRs
6Releases
575Commits
7Commit identities
species-distribution-modellingspecies-interactionsmachine-learningdeep-learninggpu-acceleration
License file reads as GPL-3.0 · 575 commits · Last activity 2026-10-17 · 0% stars, 30d
Responsiveness
How these are sampled
PRs merged (all time)
94%
Median days to close, 50 most recently updated closed issues
64
Median days to close, 50 most recently updated closed PRs
0

Stars over time

2025-08-28 · 702026-07-07 · 79
PracticesBeta

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

Checks run against github.com/theoreticalecology/s-jsdm on 2026-10-21.

Continuous integration (2)
GitHub ActionsR CMD check workflow

The R CMD check workflow runs on Linux, macOS and Windows, and on R-devel

Docs source (2)
README.Rmd

GitHub Pages site last deployed 2024-07-30

Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v4 (2026-10-20)

Dependencies

Declared dependencies
19 external dependencies (excludes base and recommended)

Installing sjSDM adds 62 packages (32 with compiled code, 52 MB of source tarballs). Heaviest: ggplot2 6.0 MB, bslib 5.6 MB, qgam 3.9 MB.

Depends (1)
R >= 4.1.0
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (3)
Author, Maintainer since 1.0.0 (2022)
Contributor
Releases (8)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • 1.0.7Latest
    record
    2025-09-17 · current release · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • 1.0.6
    record
    2024-08-19 · diff ↗ ·
    removed 2 exports
    importance, plotInternalStructure
    added 2 exports
    internalStructure, plotAssemblyEffects
  • R
    R 4.4.0 released · 2024-04-24
  • unarchivedReturned to CRAN
    2023-06-18
  • 1.0.5
    record
    2023-06-18 · diff ↗
  • archivedRemoved from CRAN
    2023-05-07
    requires archived package 'ggtern'
  • R
    R 4.3.0 released · 2023-04-21
  • 1.0.4
    record
    2023-03-30 · diff ↗ ·
    added 2 exports
    getCor, plotInternalStructure
  • 1.0.3
    record
    2022-09-14 · diff ↗
  • 1.0.2
    record
    2022-06-24 · diff ↗
  • R
    R 4.2.0 released · 2022-04-22
  • 1.0.1
    record
    2022-03-11 · diff ↗
  • 1.0.0
    record
    2022-01-10
  • R
    R 4.1.0 released · 2021-05-18

Package metadata

First published
2022-01-10
Total releases
8 / 4 yrs
License
GPL-3 OSI
Minimum R
≥ 4.1.0
Bundled data
72 KB / 2 files
Download size
1.2 MB

Cite

Cite this package

Run in R for the authors' entry:

citation("sjSDM")

The package provides a citation file, so citation() returns the authors' own entry.

It points to 10.1111/2041-210x.13687.

Cite the R Observatory

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

APA

Balamuta, J. J. (2026). R Observatory: Metrics for sjSDM version 1.0.7 [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.

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