tinyvast

Expressive interface for multivariate spatio-temporal models

https://github.com/vast-lib/tinyvast

Science Score: 49.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
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.zenodo.json file
Found .zenodo.json file
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DOI references
Found 8 DOI reference(s) in README
✓
Academic publication links
Links to: arxiv.org
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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 (11.7%) to scientific vocabulary

Keywords

vector-autoregressive-spatio-temporal-model

Last synced: 10 months ago · JSON representation

Repository

Expressive interface for multivariate spatio-temporal models

Basic Info

Host: GitHub
Owner: vast-lib
License: gpl-3.0
Language: R
Default Branch: main
Homepage: https://vast-lib.github.io/tinyVAST/
Size: 31.7 MB

Statistics

Stars: 16
Watchers: 8
Forks: 2
Open Issues: 3
Releases: 11

Topics

vector-autoregressive-spatio-temporal-model

Created over 2 years ago · Last pushed 10 months ago

Metadata Files

Readme Changelog License

README.Rmd

---
output: 
  github_document:
    toc: true
    toc_depth: 3
    df_print: "tibble"
    includes:
      in_header: header.md
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "50%",
  cache = FALSE,
  autodep = TRUE,
  dpi = 72
)
```
    
## Installation

tinyVAST can be installed from GitHub:

```{r, eval=FALSE}
library(devtools)
install_github("vast-lib/tinyVAST", dependencies = TRUE)
```


## Citation

To cite tinyVAST in publications use:

```r
citation("tinyVAST")
```

Thorson, J. T., Anderson, S. C., Goddard, P., & Rooper, C. N. (2024).
tinyVAST: R package with an expressive interface to specify lagged
and simultaneous effects in multivariate spatio-temporal models
(arXiv:2401.10193). arXiv. 



## Related software

tinyVAST is builds upon many packages. This includes [VAST](https://github.com/James-Thorson-NOAA/VAST) R package:

Thorson, J.T. 2019. Guidance for decisions using the Vector Autoregressive Spatio-Temporal (VAST) package in stock, ecosystem, habitat and climate assessments. Fisheries Research 210: 143–161. .

and [sdmTMB](https://github.com/pbs-assess/sdmTMB) R package:

Anderson, S.C., E.J. Ward, P.A. English, L.A.K. Barnett. 2022. sdmTMB: an R package for fast, flexible, and user-friendly generalized linear mixed effects models with spatial and spatiotemporal random fields. bioRxiv 2022.03.24.485545; doi: https://doi.org/10.1101/2022.03.24.485545

and the [glmmTMB](https://github.com/glmmTMB/glmmTMB) R package:

Brooks, M.E., Kristensen, K., van Benthem, K.J., Magnusson, A., Berg, C.W., Nielsen, A., Skaug, H.J., Maechler, M., and Bolker, B.M. 2017. glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R Journal 9(2): 378–400. .

[INLA](https://www.r-inla.org/) and [inlabru](https://sites.google.com/inlabru.org/inlabru) can fit many of the same models as sdmTMB (and many more) in an approximate Bayesian inference framework.

[mgcv](https://cran.r-project.org/package=mgcv) can fit similar SPDE-based Gaussian random field models with code included in [Miller et al. (2019)](https://doi.org/10.1007/s13253-019-00377-z).

Owner

Name: vast-lib
Login: vast-lib
Kind: organization

Repositories: 1
Profile: https://github.com/vast-lib

GitHub Events

Total

Create event: 15
Release event: 5
Issues event: 16
Watch event: 4
Delete event: 9
Member event: 1
Issue comment event: 33
Push event: 232
Gollum event: 2
Pull request event: 19

Last Year

Create event: 15
Release event: 5
Issues event: 16
Watch event: 4
Delete event: 9
Member event: 1
Issue comment event: 33
Push event: 232
Gollum event: 2
Pull request event: 19

Issues and Pull Requests

Last synced: 10 months ago

All Time

Total issues: 28
Total pull requests: 46
Average time to close issues: about 2 months
Average time to close pull requests: 1 day
Total issue authors: 11
Total pull request authors: 3
Average comments per issue: 3.68
Average comments per pull request: 0.54
Merged pull requests: 30
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 9
Pull requests: 18
Average time to close issues: 7 days
Average time to close pull requests: 3 days
Issue authors: 6
Pull request authors: 3
Average comments per issue: 2.22
Average comments per pull request: 0.39
Merged pull requests: 14
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

seananderson (8)
James-Thorson-NOAA (6)
PeriGerson (3)
ACharsley (3)
agruss2 (2)
sjhong0117 (1)
quantifish (1)
samc1088 (1)
reumj (1)
James-Thorson (1)

Pull Request Authors

James-Thorson-NOAA (49)
seananderson (11)
James-Thorson (2)

Top Labels

Issue Labels

enhancement (6)

Pull Request Labels

Packages

Total packages: 1
Total downloads:
- cran 278 last-month

Total dependent packages: 0
Total dependent repositories: 0
Total versions: 5
Total maintainers: 1

cran.r-project.org: tinyVAST

Multivariate Spatio-Temporal Models using Structural Equations

Homepage: https://vast-lib.github.io/tinyVAST/
Documentation: http://cran.r-project.org/web/packages/tinyVAST/tinyVAST.pdf
License: GPL-3
Latest release: 1.2.0
published 11 months ago

Versions: 5
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 278 Last month

Rankings

Stargazers count: 15.2%

Forks count: 17.4%

Dependent packages count: 27.0%

Dependent repos count: 33.3%

Average: 36.0%

Downloads: 87.0%

Maintainers (1)

James.Thorson@noaa.gov