elcic

A robust and consistent model selection criterion

https://github.com/chencxxy28/elcic

Science Score: 10.0%

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

  • CITATION.cff file
  • codemeta.json file
  • .zenodo.json file
  • DOI references
  • Academic publication links
    Links to: arxiv.org
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (10.6%) to scientific vocabulary
Last synced: 10 months ago · JSON representation

Repository

A robust and consistent model selection criterion

Basic Info
  • Host: GitHub
  • Owner: chencxxy28
  • Language: R
  • Default Branch: master
  • Size: 447 KB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created over 5 years ago · Last pushed over 3 years ago
Metadata Files
Readme

README.md

ELCIC: Empirical Likelihood-based Consistent Information Criterion

codecov R-CMD-check CRAN_Status_Badge

Conventional likelihood-based information criteria for model selection rely on the distribution assumption of data. However, for complex data that are increasingly available in many scientific fields, the specification of their underlying distribution turns out to be challenging, and the existing criteria may be limited and are not general enough to handle a variety of model selection problems. We proposed a robust and consistent model selection criterion, named as ELCIC, based upon the empirical likelihood function which is data-driven. In particular, this framework adopts plug-in estimators that can be achieved by solving external estimating equations, not limited to the empirical likelihood, which avoids potential computational convergence issues and allows versatile applications, such as generalized linear models, generalized estimating equations, penalized regressions, and so on. The formulation of our proposed criterion is initially derived from the asymptotic expansion of the marginal likelihood under the variable selection framework, but more importantly, the consistent model selection property is established under a general context.

ELCIC offers a robust model assessment and can be applied to address more complicated situations where existing methods fail to work.

How to cite ELCIC

Please cite the following publication: Chixiang Chen, Ming Wang, Rongling Wu, and Runze, Li, A Robust Consistent Information Criterion for Model Selection based on Empirical Likelihood https://arxiv.org/pdf/2006.13281.pdf

Installation

r if (!require("devtools")) { install.packages("devtools") } devtools::install_github("chencxxy28/ELCIC")

Vignettes

Please visit Tutorial

Owner

  • Login: chencxxy28
  • Kind: user

GitHub Events

Total
Last Year

Committers

Last synced: over 2 years ago

All Time
  • Total Commits: 541
  • Total Committers: 3
  • Avg Commits per committer: 180.333
  • Development Distribution Score (DDS): 0.03
Past Year
  • Commits: 24
  • Committers: 2
  • Avg Commits per committer: 12.0
  • Development Distribution Score (DDS): 0.458
Top Committers
Name Email Commits
chencxxy28 c****8@g****m 525
chencxxy28 7****8 15
Chixiang.Chen c****n@E****l 1

Issues and Pull Requests

Last synced: over 2 years ago

All Time
  • Total issues: 0
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 0
  • Total 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
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
Top Authors
Issue Authors
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 243 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 2
  • Total maintainers: 1
cran.r-project.org: ELCIC

The Empirical Likelihood-Based Consistent Information Criterion

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 243 Last month
Rankings
Forks count: 28.8%
Dependent packages count: 29.8%
Stargazers count: 35.2%
Dependent repos count: 35.5%
Average: 37.1%
Downloads: 56.1%
Maintainers (1)
Last synced: about 2 years ago

Dependencies

.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v2 composite
  • actions/upload-artifact main composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/r.yml actions
  • actions/checkout v2 composite
  • r-lib/actions/setup-r f57f1301a053485946083d7a45022b278929a78a composite
DESCRIPTION cran
  • R >= 3.5.0 depends
  • MASS * imports
  • PoisNor * imports
  • bindata * imports
  • geepack * imports
  • mvtnorm * imports
  • wgeesel * imports
  • knitr * suggests
  • markdown * suggests
  • rmarkdown * suggests
  • testthat >= 3.0.0 suggests