Copulas.jl

Copulas.jl: A fully Distributions.jl-compliant copula package - Published in JOSS (2024)

https://github.com/lrnv/copulas.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 4 DOI reference(s) in README and JOSS metadata
✓
Academic publication links
Links to: joss.theoj.org, zenodo.org
✓
Committers with academic emails
1 of 13 committers (7.7%) from academic institutions
○
Institutional organization owner
✓
JOSS paper metadata
Published in Journal of Open Source Software

Keywords

copula julia

Keywords from Contributors

pde meshing standardization interpretability eeg ecology pipelines climate-change fluxes graphics

Scientific Fields

Engineering Computer Science - 40% confidence

Last synced: 4 months ago · JSON representation ·

Repository

A fully `Distributions.jl`-compliant copula package

Basic Info

Host: GitHub
Owner: lrnv
License: mit
Language: Julia
Default Branch: main
Homepage: https://lrnv.github.io/Copulas.jl/
Size: 14.5 MB

Statistics

Stars: 103
Watchers: 3
Forks: 10
Open Issues: 33
Releases: 31

Topics

copula julia

Created almost 4 years ago · Last pushed 4 months ago

Metadata Files

Readme License Citation

Copulas.jl

A fully `Distributions.jl`-compliant copula package

Copulas.jl brings most standard copula features into native Julia: random number generation, pdf and cdf, fitting, copula-based multivariate distributions through Sklar's theorem, etc. Since copulas are distribution functions, we fully comply with the Distributions.jl API. This allows interoperability with the broader ecosystem, based on this API, such as, e.g., Turing.jl.

Usually, people that use and work with copulas turn to R, because of the amazing package R::copula. While well-maintained and regularly updated, R::copula is a mixture of obscure, heavily optimized C code and more standard R code, which makes it a complicated code base for readability, extensibility, reliability and maintenance.

This is an attempt to provide a very light, fast, reliable and maintainable copula implementation in native Julia. One of the notable benefits of such a native implementation (among others) is the floating point type agnosticity, i.e. compatibility with BigFloat, DoubleFloats, MultiFloats, etc.

The package revolves around two main types:

Copula, an abstract mother type for all the copulas in the package
SklarDist, a distribution type that allows construction of a multivariate distribution by specifying the copula and the marginals through Sklar's theorem.

Warning: This is fairly experimental work, use with caution.

Getting started

The package is registered in Julia's General registry so you may simply install the package by running :

julia ] add Copulas

The API contains random number generation, cdf and pdf evaluation, and the fit function from Distributions.jl. A typical use case might look like this:

```julia using Copulas, Distributions, Random X₁ = Gamma(2,3) X₂ = Pareto() X₃ = LogNormal(0,1) C = ClaytonCopula(3,0.7) # A 3-variate Clayton Copula with θ = 0.7 D = SklarDist(C,(X₁,X₂,X₃)) # The final distribution

simu = rand(D,1000) # Generate a dataset

You may estimate a copula using the `fit` function:

D̂ = fit(SklarDist{ClaytonCopula,Tuple{Gamma,Normal,LogNormal}}, simu) ```

The list of availiable copula models is very large, check it out on our documentation !

The general implementation philosophy is for the code to follow the mathematical boundaries of the implemented concepts. For example, this is the only implementation we know (in any language) that allows for all Archimedean copulas to be sampled: we use the Williamson transformation for non-standard generators, including user-provided black-box ones.

Feature comparison

There are competing packages in Julia, such as BivariateCopulas.jl which only deals with a few models in bivariate settings but has very nice graphs, or DatagenCopulaBased.jl, which only provides sampling and does not have exactly the same models as Copulas.jl. While not fully covering out both of these package's functionality (mostly because the three projects chose different implementation paths), Copulas.jl brings, as a key feature, the compliance with the broader ecosystem. The following table provides a feature comparison between the three:

| | Copulas.jl | DatagenCopulaBased.jl | BivariateCopulas.jl | |----------------|--------------|-------------------------|-----------------------| | Distributions.jl's API | ✔️ | ❌ | ✔️ | | Fitting | ✔️ | ❌ | ❌ | | Plotting | ❌ | ❌ | ✔️ | | Available copulas | | | | | - Classic Bivariate | ✔️ | ✔️ | ✔️ | | - Classic Multivariate | ✔️ | ✔️ | ❌ | | - Archimedeans | ✔️ (All of them) | ⚠️ Selected ones | ⚠️Selected ones | | - Bivariate Extreme Value| ✔️ | ❌ | ❌ | | - Obscure Bivariate | ✔️ | ❌ | ❌ | | - Archimedean Chains | ❌ | ✔️ | ❌ |

Since our primary target is maintainability and readability of the implementation, we did not consider the efficiency and the performance of the code yet. Proper benchmarks will come in the near future.

Contributions are welcome

If you want to contribute to the package, ask a question, found a bug or simply want to chat, do not hesitate to open an issue on this repo. General guidelines on collaborative practices (colprac) are available at https://github.com/SciML/ColPrac.

Citation

Do not hesitate to star this repository to show support. If you use this package in your researches, please cite it with the following bibtex code:

bibtex @article{LavernyJimenez2024, author = {Oskar Laverny and Santiago Jimenez}, title = {Copulas.jl: A fully Distributions.jl-compliant copula package}, journal = {Journal of Open Source Software}, doi = {10.21105/joss.06189}, url = {https://doi.org/10.21105/joss.06189}, year = {2024}, publisher = {The Open Journal}, volume = {9}, number = {94}, pages = {6189} }

Owner

Name: Oskar Laverny
Login: lrnv
Kind: user
Location: Brussels
Company: UCLouvain

Website: actuarial.science
Repositories: 5
Profile: https://github.com/lrnv

What would be the dependence structure between quality of code and quantity of coffee ?

JOSS Publication

Copulas.jl: A fully Distributions.jl-compliant copula package

Published

February 29, 2024

DOI

10.21105/joss.06189

Volume 9, Issue 94, Page 6189

Authors

Oskar Laverny

Aix Marseille Univ, Inserm, IRD, SESSTIM, Sciences Economiques & Sociales de la Santé & Traitement de l’Information Médicale, ISSPAM, Marseille, France.

Santiago Jimenez

Federal University of Pernambuco

Editor

Øystein Sørensen

Citation (CITATION.bib)

@article{Laverny2024, 
    doi = {10.21105/joss.06189}, 
    url = {https://doi.org/10.21105/joss.06189}, 
    year = {2024}, 
    publisher = {The Open Journal}, 
    volume = {9}, 
    number = {94}, 
    pages = {6189}, 
    author = {Oskar Laverny and Santiago Jimenez}, 
    title = {Copulas.jl: A fully Distributions.jl-compliant copula package}, journal = {Journal of Open Source Software}
}

GitHub Events

Total

Create event: 22
Commit comment event: 9
Release event: 4
Issues event: 15
Watch event: 15
Delete event: 10
Issue comment event: 75
Push event: 49
Pull request review event: 12
Pull request review comment event: 15
Pull request event: 30
Fork event: 1

Last Year

Create event: 28
Commit comment event: 9
Release event: 4
Issues event: 15
Watch event: 15
Delete event: 14
Issue comment event: 77
Push event: 54
Pull request review event: 12
Pull request review comment event: 15
Pull request event: 39
Fork event: 1

Committers

Last synced: 5 months ago

All Time

Total Commits: 360
Total Committers: 13
Avg Commits per committer: 27.692
Development Distribution Score (DDS): 0.142

Past Year

Commits: 33
Committers: 5
Avg Commits per committer: 6.6
Development Distribution Score (DDS): 0.182

Top Committers

Name	Email	Commits
Oskar Laverny	o**y@g**m	309
Santymax98	1****8	15
CompatHelper Julia	c**y@j**g	10
dependabot[bot]	4****]	8
github-actions[bot]	4****]	5
Øystein Sørensen	o**n@h**m	4
szcf-weiya	s**a@g**m	2
mlkrock	m**k@c**u	2
pdeffebach	2****h	1
Leandro Martínez	3****q	1
Jasper Behrensdorf	j**r@b**e	1
Herb Susmann	h**0@g**m	1
Dilum Aluthge	d**m@a**m	1

Committer Domains (Top 20 + Academic)

aluthge.com: 1 behrensdorf.de: 1 colorado.edu: 1 julialang.org: 1

Issues and Pull Requests

Last synced: 4 months ago

All Time

Total issues: 90
Total pull requests: 245
Average time to close issues: about 1 month
Average time to close pull requests: 9 days
Total issue authors: 18
Total pull request authors: 12
Average comments per issue: 1.78
Average comments per pull request: 1.41
Merged pull requests: 202
Bot issues: 0
Bot pull requests: 34

Past Year

Issues: 10
Pull requests: 65
Average time to close issues: 3 days
Average time to close pull requests: 8 days
Issue authors: 4
Pull request authors: 6
Average comments per issue: 0.7
Average comments per pull request: 1.69
Merged pull requests: 46
Bot issues: 0
Bot pull requests: 9

View more stats

Top Authors

Issue Authors

lrnv (64)
Santymax98 (7)
rand5 (3)
osorensen (2)
droodman (1)
PharmCat (1)
DomDF (1)
JuliaTagBot (1)
EthanRLeonard (1)
mlkrock (1)
lidiamandre (1)
alecloudenback (1)
andreasnoack (1)
HJW019 (1)
Vaibhavdixit02 (1)

Pull Request Authors

lrnv (168)
Santymax98 (23)
github-actions[bot] (20)
dependabot[bot] (14)
osorensen (8)
szcf-weiya (2)
DilumAluthge (2)
lmiq (2)
pdeffebach (2)
mlkrock (2)
herbps10 (1)
FriesischScott (1)

Top Labels

Issue Labels

JOSS (8) bug (7) good first issue (3) enhancement (2) documentation (2)

Pull Request Labels

dependencies (14) github_actions (1)

Packages

Total packages: 1
Total downloads:
- julia 257 total

Total dependent packages: 2
Total dependent repositories: 0
Total versions: 31

juliahub.com: Copulas

A fully `Distributions.jl`-compliant copula package

Homepage: https://lrnv.github.io/Copulas.jl/
Documentation: https://docs.juliahub.com/General/Copulas/stable/
License: MIT
Latest release: 0.1.30
published 6 months ago

Versions: 31
Dependent Packages: 2
Dependent Repositories: 0
Downloads: 257 Total

Rankings

Dependent repos count: 9.9%

Stargazers count: 15.0%

Average: 19.0%

Dependent packages count: 23.0%

Forks count: 28.1%

Last synced: 4 months ago

Dependencies

.github/workflows/CI.yml actions

actions/checkout v2 composite
codecov/codecov-action v2 composite
julia-actions/cache v1 composite
julia-actions/julia-buildpkg v1 composite
julia-actions/julia-docdeploy v1 composite
julia-actions/julia-processcoverage v1 composite
julia-actions/julia-runtest v1 composite
julia-actions/setup-julia v1 composite

.github/workflows/CompatHelper.yml actions

.github/workflows/TagBot.yml actions

JuliaRegistries/TagBot v1 composite

.github/workflows/register.yml actions

julia-actions/RegisterAction latest composite

.github/workflows/draft_paper.yml actions

actions/checkout v4 composite
actions/upload-artifact v1 composite
openjournals/openjournals-draft-action master composite

Copulas.jl

Science Score: 100.0%

Keywords

Keywords from Contributors

Scientific Fields

Repository

Basic Info

Statistics

Topics

Metadata Files

README.md

Copulas.jl

Getting started

You may estimate a copula using the fit function:

Feature comparison

Contributions are welcome

Citation

Owner

JOSS Publication

Copulas.jl: A fully Distributions.jl-compliant copula package

Authors

Editor

Tags

Citation (CITATION.bib)

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

juliahub.com: Copulas

Rankings

Dependencies

You may estimate a copula using the `fit` function: