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Kirstine.jl

Kirstine.jl: A Julia Package for Bayesian Optimal Design of Experiments - Published in JOSS (2024)

https://github.com/lsandig/kirstine.jl

Science Score: 100.0%

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

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 3 DOI reference(s) in README and JOSS metadata
  • ✓
    Academic publication links
    Links to: joss.theoj.org
  • ✓
    Committers with academic emails
    1 of 1 committers (100.0%) from academic institutions
  • ○
    Institutional organization owner
  • ✓
    JOSS paper metadata
    Published in Journal of Open Source Software

Scientific Fields

Earth and Environmental Sciences Physical Sciences - 40% confidence
Economics Social Sciences - 40% confidence
Last synced: 4 months ago · JSON representation ·

Repository

Bayesian optimal design of experiments in Julia. Note: This is just a mirror of the main branch for the Julia General registry. Development happens at sourcehut. Please report any issues over there.

Basic Info
Statistics
  • Stars: 3
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 2 years ago · Last pushed 10 months ago
Metadata Files
Readme License Citation

README.md

Kirstine.jl

A Julia package for Bayesian optimal experimental design with nonlinear regression models.

repo | docs | change log | examples | mailing lists

Project Status

Beta. Mostly stable, breaking changes will be mostly cosmetic.

Features

  • arbitrary nonlinear regression models
  • scalar or vector-valued response variable
  • variance-covariance matrix may depend on covariate
  • Bayesian and locally optimal design
  • design criteria: D, A
  • composite design problems
  • separation of design variables and model covariates
  • particle swarm optimization
  • direct maximization and exchange algorithm
  • modular and extendable
  • minimal dependencies

Installation

Kirstine.jl is in the General Julia package registry. You can install it with

julia Pkg.add("Kirstine")

Alternatively, you can get it directly from sourcehut:

julia Pkg.add(url = "https://git.sr.ht/~lsandig/Kirstine.jl")

To install the development branch: julia Pkg.add(url = "https://git.sr.ht/~lsandig/Kirstine.jl", rev="develop")

Documentation

Markdown, HTML

To get started, read the tutorial.

For a change log, see the list of annotated tags.

There is also a separate repository with additional examples.

License

Kirstine.jl is free and open source software. The code is licensed under GPL-3.0 or later, and the documentation under GFDL-1.3 or later.

Citing

Kirstine.jl is published in the Journal of Open Source Software. You can cite the package like this:

@article{, author = {Ludger Sandig}, title = {Kirstine.jl: A Julia Package for Bayesian Optimal Design of Experiments}, journal = {Journal of Open Source Software}, volume = 9, number = 97, pages = 6424, year = 2024, doi = {10.21105/joss.06424}, }

Rationale

Why yet another package for optimal design?

In R, there is already the ICAOD package for finding optimal designs in any model of which you can implement the Fisher information matrix. However, it is not as efficient as it could be and the code base is hard to extend for more complicated design problems. There are also various other packages (e.g., DoseFinding or PopED) for optimal design with special criteria or special kinds of nonlinear regression models. In Julia, there is already ExperimentalDesign.jl for block, factorial and response-surface designs in linear regression/ANOVA and polynomial regression models.

Kirstine.jl is an attempt to provide applied statisticians with a Julia package for optimal design in arbitrary nonlinear regression models. Its development goals are speed and modularity, as well as a small, stable and well-documented code base.

Contributing

The source code of Kirstine.jl is managed on sourcehut.

Please post usage questions and general discussion on the kirstine-users mailing list.

Only bug reports should be filed on the issue tracker.

Patches are welcome and should be submitted via git send-email to the kirstine-devel mailing list. Please make sure that your patch does not break any existing tests and includes new tests for any functionality it adds.

Owner

  • Name: Ludger Sandig
  • Login: lsandig
  • Kind: user
  • Location: Germany

JOSS Publication

Kirstine.jl: A Julia Package for Bayesian Optimal Design of Experiments
Published
May 20, 2024
DOI
Volume 9, Issue 97, Page 6424
Authors
Ludger Sandig ORCID
Department of Statistics, TU Dortmund University, Germany
Editor
Jonny Saunders ORCID
Tags
design of experiments Bayesian statistics
View PDF Review Thread Software Archive

Citation (CITATION.cff) 

cff-version: "1.2.0"
authors:
- family-names: Sandig
  given-names: Ludger
  orcid: "https://orcid.org/0000-0002-3174-3275"
doi: 10.5281/zenodo.11185430
message: If you use this software, please cite our article in the
  Journal of Open Source Software.
preferred-citation:
  authors:
  - family-names: Sandig
    given-names: Ludger
    orcid: "https://orcid.org/0000-0002-3174-3275"
  date-published: 2024-05-20
  doi: 10.21105/joss.06424
  issn: 2475-9066
  issue: 97
  journal: Journal of Open Source Software
  publisher:
    name: Open Journals
  start: 6424
  title: "Kirstine.jl: A Julia Package for Bayesian Optimal Design of
    Experiments"
  type: article
  url: "https://joss.theoj.org/papers/10.21105/joss.06424"
  volume: 9
title: "Kirstine.jl: A Julia Package for Bayesian Optimal Design of
  Experiments"

GitHub Events

Total
  • Commit comment event: 2
Last Year
  • Commit comment event: 2

Committers

Last synced: 5 months ago

All Time
  • Total Commits: 564
  • Total Committers: 1
  • Avg Commits per committer: 564.0
  • Development Distribution Score (DDS): 0.0
Past Year
  • Commits: 137
  • Committers: 1
  • Avg Commits per committer: 137.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
lsandig l****g@u****u 564
Committer Domains (Top 20 + Academic)
udo.edu: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time
  • Total issues: 4
  • Total pull requests: 0
  • Average time to close issues: 28 days
  • Average time to close pull requests: N/A
  • Total issue authors: 3
  • Total pull request authors: 0
  • Average comments per issue: 2.25
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • 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
  • roualdes (2)
  • trappmartin (1)
  • harisorgn (1)
Pull Request Authors
Top Labels
Issue Labels
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Packages

  • Total packages: 1
  • Total downloads: unknown
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 5
juliahub.com: Kirstine

Bayesian optimal design of experiments in Julia. Note: This is just a mirror of the main branch for the Julia General registry. Development happens at sourcehut. Please report any issues over there.

  • Versions: 5
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent repos count: 10.1%
Average: 25.3%
Dependent packages count: 40.4%
Last synced: 4 months ago