https://github.com/csiro/dstsom
Dynamic Spatio-Temporal Sequential Ordinal Models
Science Score: 39.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 4 DOI reference(s) in README -
○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (6.0%) to scientific vocabulary
Repository
Dynamic Spatio-Temporal Sequential Ordinal Models
Basic Info
- Host: GitHub
- Owner: csiro
- License: other
- Language: R
- Default Branch: main
- Size: 6.22 MB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Copyright (c) 2024 Commonwealth Scientific and Industrial Research Organisation (CSIRO) ABN 41 687 119 230.
This code is released under a General Public License, version 3 or any higher
version as noted in the license field of the DESCRIPTION file. You can obtain a
copy of the GPLv3 license at https://www.gnu.org/licenses/gpl-3.0.en.html or
by executing RShowDoc("GPL-3") in R.
CSIRO does not make any guarantees of accuracy or relevance of the code. CSIRO does not guarantee the code has no security vulnerabilities. CSIRO does not guarantee to bug-fix or security-fix the code. CSIRO reserves the right to "retire" the code and make no further changes.
Please see DESCRIPTION file for further information on this code. Please see LICENSE file for information on data licenses. This package provides Supplementary Information to the arXiv document at https://doi.org/10.48550/arXiv.2509.01976, see file vignettes/DSTSOM.pdf.
To cite this package use:
Hosack GR, Yang W, Pike KN (2025). DSTSOM: Dynamic Spatio-Temporal Sequential Ordinal Models. R package version 0.1.0.
Hosack GR, Yang W, Pike KN, O'Loughlin LS, Cook E, Howland B, Sutcliffe E, Milner RNC, Gooden B, Froese JG (2025). “Dynamic Spatio-Temporal Sequential Ordinal Models: Application to Invasive Weeds.” arXiv. arXiv:2509.01976 [stat.AP], https://doi.org/10.48550/arXiv.2509.01976.
Owner
- Name: CSIRO
- Login: csiro
- Kind: organization
- Location: Australia
- Repositories: 2
- Profile: https://github.com/csiro
CSIRO public facing GitHub organisation.
GitHub Events
Total
- Push event: 1
Last Year
- Push event: 1
Dependencies
- INLA * imports
- fmesher * imports
- matrixStats * imports
- rasterVis * imports
- sf * imports
- terra * imports
- VGAM * suggests
- catdata * suggests
- knitr * suggests
- rms * suggests
- utils * suggests
- xtable * suggests