The jagstargets R package

The jagstargets R package: a reproducible workflow framework for Bayesian data analysis with JAGS - Published in JOSS (2021)

https://github.com/ropensci/jagstargets

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Published in Journal of Open Source Software

Keywords

bayesian high-performance-computing jags make r r-targetopia reproducibility rjags rstats rstats-package statistics targets

Keywords from Contributors

drake makefile ropensci

Last synced: 4 months ago · JSON representation

Repository

Reproducible Bayesian data analysis pipelines with targets and JAGS

Basic Info

Host: GitHub
Owner: ropensci
License: other
Language: R
Default Branch: main
Homepage: https://docs.ropensci.org/jagstargets
Size: 613 KB

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Stars: 11
Watchers: 3
Forks: 7
Open Issues: 0
Releases: 11

Topics

bayesian high-performance-computing jags make r r-targetopia reproducibility rjags rstats rstats-package statistics targets

Created about 5 years ago · Last pushed about 1 year ago

Metadata Files

Readme Changelog Contributing License Codemeta Zenodo

README.Rmd

---
output: github_document
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# jagstargets 

[![JOSS](https://joss.theoj.org/papers/759f48d9ae7bc57e318e2d0ecc00569e/status.svg)](https://joss.theoj.org/papers/10.21105/joss.03877)
[![ropensci](https://badges.ropensci.org/425_status.svg)](https://github.com/ropensci/software-review/issues/425)
[![DOI](https://zenodo.org/badge/321076424.svg)](https://zenodo.org/badge/latestdoi/321076424)
[![R Targetopia](https://img.shields.io/badge/R_Targetopia-member-blue?style=flat&labelColor=gray)](https://wlandau.github.io/targetopia/)
[![cran](https://www.r-pkg.org/badges/version/jagstargets)](https://cran.r-project.org/package=jagstargets)
[![status](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)
[![check](https://github.com/ropensci/jagstargets/workflows/check/badge.svg)](https://github.com/ropensci/jagstargets/actions?query=workflow%3Acheck)
[![codecov](https://codecov.io/gh/ropensci/jagstargets/branch/main/graph/badge.svg?token=3T5DlLwUVl)](https://app.codecov.io/gh/ropensci/gittargets)
[![lint](https://github.com/ropensci/jagstargets/workflows/lint/badge.svg)](https://github.com/ropensci/jagstargets/actions?query=workflow%3Alint)

Bayesian data analysis usually incurs long runtimes and cumbersome custom code, and the process of prototyping and deploying custom [JAGS](https://mcmc-jags.sourceforge.io) models can become a daunting software engineering challenge. To ease this burden, the `jagstargets` R package creates [JAGS](https://mcmc-jags.sourceforge.io) pipelines that are concise, efficient, scalable, and tailored to the needs of Bayesian statisticians. Leveraging [`targets`](https://docs.ropensci.org/targets/), `jagstargets` pipelines automatically parallelize the computation and skip expensive steps when the results are already up to date. Minimal custom user-side code is required, and there is no need to manually configure branching, so `jagstargets` is easier to use than [`targets`](https://docs.ropensci.org/targets/) and [`R2jags`](https://CRAN.R-project.org/package=R2jags) directly.

## Prerequisites

1. The [prerequisites of the `targets` R package](https://docs.ropensci.org/targets/#prerequisites).
1. Basic familiarity with [`targets`](https://docs.ropensci.org/targets/): watch minutes 7 through 40 of [this video](https://youtu.be/Gqn7Xn4d5NI?t=439), then read [this chapter](https://books.ropensci.org/targets/walkthrough.html) of the [user manual](https://books.ropensci.org/targets/).
1. Familiarity with Bayesian Statistics and [JAGS](https://mcmc-jags.sourceforge.io/). Prior knowledge of [`rjags`](https://cran.r-project.org/package=rjags) or [`R2jags`](https://cran.r-project.org/package=R2jags) helps.

## How to get started

Read the `jagstargets` [introductory vignette](https://docs.ropensci.org/jagstargets/articles/introduction.html), and then use  as a reference while constructing your own workflows. If you need to analyze large collections of simulated datasets, please consult the [simulation vignette](https://docs.ropensci.org/jagstargets/articles/simulation.html).

## Installation

`jagstargets` requires the user to install [JAGS](https://mcmc-jags.sourceforge.io/), [`rjags`](https://CRAN.R-project.org/package=rjags), and [`R2jags`](https://CRAN.R-project.org/package=R2jags) beforehand. You can install JAGS from , and you can install the rest from CRAN.

```{r, eval = FALSE}
install.packages(c("rjags", "R2jags"))
```

Then, install the latest release from CRAN.

```{r, eval = FALSE}
install.packages("jagstargets")
```

Alternatively, install the GitHub development version to access the latest features and patches.

```{r, eval = FALSE}
install.packages("remotes")
remotes::install_github("ropensci/jagstargets")
```

## Usage

Begin with one or more models: for example, the simple regression model below with response variable $y$ and covariate $x$.





Next, write a JAGS model file for each model like the `model.jags` file below.

```jags
model {
  for (i in 1:n) {
    y[i] ~ dnorm(x[i] * beta, 1)
  }
  beta ~ dnorm(0, 1)
}
```

To begin a reproducible analysis pipeline with this model, write a [`_targets.R` file](https://books.ropensci.org/targets/walkthrough.html) that loads your packages, defines a function to generate JAGS data, and lists a pipeline of targets. The target list can call target factories like [`tar_jags()`](https://docs.ropensci.org/jagstargets/reference/tar_jags.html) as well as ordinary targets with [`tar_target()`](https://docs.ropensci.org/targets/reference/tar_target.html). The following minimal example is simple enough to contain entirely within the `_targets.R` file, but for larger projects, you may wish to store functions in separate files as in the [`targets-stan`](https://github.com/wlandau/targets-stan) example.

```{r, eval = FALSE}
# _targets.R
library(targets)
library(jagstargets)

generate_data <- function() {
  true_beta <- stats::rnorm(n = 1, mean = 0, sd = 1)
  x <- seq(from = -1, to = 1, length.out = n)
  y <- stats::rnorm(n, x * true_beta, 1)
  out <- list(n = n, x = x, y = y, true_beta = true_beta)
}

list(
  tar_jags(
    example,
    jags_files = "model.jags", # You provide this file.
    parameters.to.save = "beta",
    data = generate_data()
  )
)
```

Run [`tar_visnetwork()`](https://docs.ropensci.org/targets/reference/tar_visnetwork.html) to check `_targets.R` for correctness, then call [`tar_make()`](https://docs.ropensci.org/targets/reference/tar_make.html) to run the pipeline. Access the results using [`tar_read()`](https://docs.ropensci.org/targets/reference/tar_read.html), e.g. `tar_read(tar_read(example_summary_x)`. Visit the [introductory vignette](https://docs.ropensci.org/jagstargets/articles/introduction.html) to read more about this example.

## How the package works

`jagstargets` supports specialized [target factories](https://ropensci.org/blog/2021/02/03/targets/#target-factories) that create ensembles of [target objects](https://docs.ropensci.org/targets/reference/tar_target.html) for [`R2jags`](https://CRAN.R-project.org/package=R2jags) workflows. These [target factories](https://ropensci.org/blog/2021/02/03/targets/#target-factories) abstract away the details of [`targets`](https://docs.ropensci.org/targets/) and [`R2jags`](https://CRAN.R-project.org/package=R2jags) and make both packages easier to use. For details, please read the [introductory vignette](https://docs.ropensci.org/jagstargets/articles/introduction.html).

## Help

Please read the `targets` help guide at  to learn how to ask for help.

If you have trouble using `jagstargets`, you can ask for help in the [GitHub discussions forum](https://github.com/ropensci/jagstargets/discussions/categories/help). Because the purpose of `jagstargets` is to combine [`targets`](https://docs.ropensci.org/targets/) and [`R2jags`](https://CRAN.R-project.org/package=R2jags), your issue may have something to do with one of the latter two packages, a [dependency of `targets`](https://github.com/ropensci/targets/blob/4e3ef2a6c986f558a25e544416f480fc01236b6b/DESCRIPTION#L49-L88), or [`R2jags`](https://CRAN.R-project.org/package=R2jags) itself. When you troubleshoot, peel back as many layers as possible to isolate the problem. For example, if the issue comes from [`R2jags`](https://CRAN.R-project.org/package=R2jags), create a [reproducible example](https://reprex.tidyverse.org) that directly invokes [`R2jags`](https://CRAN.R-project.org/package=R2jags) without invoking `jagstargets`. The GitHub discussion and issue forums of those packages are great resources.

## Participation

Development is a community effort, and we welcome discussion and contribution. By participating in this project, you agree to abide by the [code of conduct](https://ropensci.org/code-of-conduct/) and the [contributing guide](https://github.com/ropensci/jagstargets/blob/main/CONTRIBUTING.md).

## Citation

```{r, warning = FALSE}
citation("jagstargets")
```

Owner

Name: rOpenSci
Login: ropensci
Kind: organization
Email: info@ropensci.org
Location: Berkeley, CA

Website: https://ropensci.org/
Twitter: rOpenSci
Repositories: 307
Profile: https://github.com/ropensci

JOSS Publication

The jagstargets R package: a reproducible workflow framework for Bayesian data analysis with JAGS

Published

December 01, 2021

DOI

10.21105/joss.03877

Volume 6, Issue 68, Page 3877

Authors

William Michael Landau

Eli Lilly and Company

Editor

Gabriela Alessio Robles

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    "https://github.com/ropensci/jagstargets/actions?query=workflow%3Acheck",
    "https://app.codecov.io/gh/ropensci/gittargets",
    "https://github.com/ropensci/jagstargets/actions?query=workflow%3Alint"
  ],
  "developmentStatus": "https://www.repostatus.org/#active",
  "review": {
    "@type": "Review",
    "url": "https://github.com/ropensci/software-review/issues/425",
    "provider": "https://ropensci.org"
  },
  "keywords": [
    "r",
    "rstats",
    "reproducibility",
    "high-performance-computing",
    "bayesian",
    "jags",
    "rjags",
    "statistics",
    "targets",
    "make",
    "rstats-package",
    "r-targetopia"
  ]
}

GitHub Events

Total

Release event: 2
Watch event: 2
Push event: 6
Fork event: 1
Create event: 2

Last Year

Release event: 2
Watch event: 2
Push event: 6
Fork event: 1
Create event: 2

Committers

Last synced: 5 months ago

All Time

Total Commits: 243
Total Committers: 6
Avg Commits per committer: 40.5
Development Distribution Score (DDS): 0.062

Past Year

Commits: 11
Committers: 2
Avg Commits per committer: 5.5
Development Distribution Score (DDS): 0.364

Top Committers

Name	Email	Commits
wlandau	w**u@g**m	228
wlandau	w**s@g**m	9
Maëlle Salmon	m**n@y**e	3
Jeroen Ooms	j**s@g**m	1
C198353-CA	3****A	1
David Lawrence Miller	g**b@n**t	1

Committer Domains (Top 20 + Academic)

ninepointeightone.net: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time

Total issues: 23
Total pull requests: 8
Average time to close issues: 28 days
Average time to close pull requests: about 12 hours
Total issue authors: 6
Total pull request authors: 5
Average comments per issue: 1.13
Average comments per pull request: 0.63
Merged pull requests: 8
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 0
Pull requests: 0
Average time to close issues: N/A
Average time to close pull requests: N/A
Issue authors: 0
Pull request authors: 0
Average comments per issue: 0
Average comments per pull request: 0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

wlandau (16)
dill (3)
JonasMoss (1)
rich-payne (1)
sachsmc (1)
AoifeHughes (1)

Pull Request Authors

maelle (5)
wlandau-lilly (2)
dill (1)
wlandau (1)
jeroen (1)

Top Labels

Issue Labels

type: new feature (6) type: bug (2) topic: documentation (2) type: maintenance (1) order: 3 (1) order: 2 (1) order: 1 (1) order: sooner (1)

Pull Request Labels

Packages

Total packages: 1
Total downloads:
- cran 721 last-month

Total dependent packages: 0
Total dependent repositories: 0
Total versions: 8
Total maintainers: 1

cran.r-project.org: jagstargets

Targets for JAGS Pipelines

Homepage: https://docs.ropensci.org/jagstargets/
Documentation: http://cran.r-project.org/web/packages/jagstargets/jagstargets.pdf
License: MIT + file LICENSE
Latest release: 1.2.2
published about 1 year ago

Versions: 8
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 721 Last month

Rankings

Forks count: 12.8%

Stargazers count: 17.9%

Average: 28.1%

Dependent packages count: 29.8%

Dependent repos count: 35.5%

Downloads: 44.5%

Maintainers (1)

will.landau.oss@gmail.com

Last synced: 4 months ago

Dependencies

DESCRIPTION cran

R >= 3.5.0 depends
R2jags >= 0.6.1 imports
coda >= 0.19.4 imports
digest >= 0.6.25 imports
fst >= 0.9.2 imports
posterior >= 1.0.1 imports
purrr >= 0.3.4 imports
qs >= 0.23.2 imports
rjags >= 4.10 imports
rlang >= 0.4.10 imports
stats * imports
tarchetypes >= 0.6.0 imports
targets >= 0.12.0 imports
tibble >= 3.0.1 imports
tools * imports
utils * imports
withr >= 2.1.2 imports
R.utils >= 2.10.1 suggests
dplyr >= 1.0.2 suggests
fs >= 1.5.0 suggests
knitr >= 1.30 suggests
rmarkdown >= 2.3 suggests
testthat >= 3.0.0 suggests
tidyr >= 1.1.2 suggests
visNetwork >= 2.0.9 suggests

.github/workflows/check.yaml actions

actions/checkout v3 composite
r-lib/actions/check-r-package v2 composite
r-lib/actions/setup-pandoc v2 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

.github/workflows/cover.yaml actions

actions/checkout v3 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

.github/workflows/lint.yaml actions

actions/checkout v3 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

The jagstargets R package

Science Score: 93.0%

Keywords

Keywords from Contributors

Repository

Basic Info

Statistics

Topics

Metadata Files

README.Rmd

Owner

JOSS Publication

The jagstargets R package: a reproducible workflow framework for Bayesian data analysis with JAGS

Authors

Editor

Tags

CodeMeta (codemeta.json)

GitHub Events

Total

Last Year

Committers

All Time

Past Year

Top Committers

Committer Domains (Top 20 + Academic)

Issues and Pull Requests

All Time

Past Year

Top Authors

Issue Authors

Pull Request Authors

Top Labels

Issue Labels

Pull Request Labels

Packages

cran.r-project.org: jagstargets

Rankings

Maintainers (1)

Dependencies