Science Score: 59.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 4 DOI reference(s) in README -
✓Academic publication links
Links to: arxiv.org -
✓Committers with academic emails
1 of 2 committers (50.0%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (11.4%) to scientific vocabulary
Last synced: 6 months ago
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JSON representation
Repository
Basic Info
- Host: GitHub
- Owner: SMAC-Group
- Language: R
- Default Branch: master
- Homepage: https://smac-group.github.io/ib/
- Size: 213 KB
Statistics
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 2
- Releases: 2
Created almost 6 years ago
· Last pushed 6 months ago
Metadata Files
Readme
Changelog
README.Rmd
---
title: ""
output: github_document
---
[](https://github.com/SMAC-Group/ib/actions)
[)`-green.svg)](https://github.com/SMAC-Group/ib)
[](https://www.gnu.org/licenses/gpl-3.0.en.html)
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
# Bias correction via the iterative bootstrap
This is an under-development package that proposes the iterative bootstrap algorithm
of [Kuk (1995)](https://doi.org/10.1111/j.2517-6161.1995.tb02035.x)
and further studied by [Guerrier et al (2019)](https://doi.org/10.1080/01621459.2017.1380031)
and [Guerrier et al (2020)](https://arxiv.org/pdf/2002.08757.pdf).
In order to install the package
```{r, installation, eval = FALSE}
## if not installed
## install.packages("remotes")
remotes::install_github("SMAC-Group/ib")
```
The `ib` package is conceived as a wrapper: an `object` that needs a bias correction is supplied to the `ib()` function. For example, for a negative binomial regression:
```{r, glm.nb, eval=FALSE}
library(ib)
library(MASS)
fit_nb <- glm.nb(Days ~ Sex/(Age + Eth*Lrn), data = quine)
fit_ib1 <- ib(fit_nb)
summary(fit_ib1)
## correct for overdispersion with H=100
fit_ib2 <- ib(fit_nb, control=list(H=100), extra_param = TRUE)
summary(fit_ib2)
```
Currently we support `lm`, `glm`, `glm.nb`, `lmer`, `nls` and `vglm` classes, as shown in the example above with the overdispersion parameter of the negative binomial regression. More details
are in `help(ib)`.
On top of `simulate`, we also consider cases where the response variable is generated using censoring, missing at random and outliers mechanisms (see `help(ibControl)` for more details). For example
```{r, glm.nb with censoring, eval=FALSE}
## suppose values above 30 are censored
quine2 <- transform(quine, Days=pmin(Days,30))
fit_nb <- glm.nb(Days ~ Sex/(Age + Eth*Lrn), data = quine2)
fit_ib1 <- ib(fit_nb, control = list(cens=TRUE, right=30))
summary(fit_ib1)
## correct for overdispersion with H=100
fit_ib2 <- ib(fit_nb, control=list(H=100, cens=TRUE, right=30), extra_param = TRUE)
summary(fit_ib2)
```
Owner
- Name: Statistical Methods, Applications & Computing Group
- Login: SMAC-Group
- Kind: organization
- Email: contact@smac-group.com
- Website: smac-group.com
- Repositories: 63
- Profile: https://github.com/SMAC-Group
GitHub Events
Total
- Delete event: 1
- Push event: 4
- Create event: 1
Last Year
- Delete event: 1
- Push event: 4
- Create event: 1
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 1
- Total pull requests: 6
- Average time to close issues: N/A
- Average time to close pull requests: 1 day
- Total issue authors: 1
- Total pull request authors: 2
- Average comments per issue: 0.0
- Average comments per pull request: 0.5
- Merged pull requests: 6
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 1
- Average time to close issues: N/A
- Average time to close pull requests: about 3 hours
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 1.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- samorso (1)
Pull Request Authors
- samorso (4)
- olivroy (2)
Top Labels
Issue Labels
enhancement (1)
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- cran 192 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 3
- Total maintainers: 1
cran.r-project.org: ib
Bias Correction via Iterative Bootstrap
- Homepage: https://smac-group.github.io/ib/
- Documentation: http://cran.r-project.org/web/packages/ib/ib.pdf
- License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
-
Latest release: 0.2.1
published 6 months ago
Rankings
Dependent repos count: 23.9%
Stargazers count: 27.8%
Forks count: 27.8%
Dependent packages count: 28.7%
Average: 32.1%
Downloads: 52.0%
Maintainers (1)
Last synced:
6 months ago
Dependencies
DESCRIPTION
cran
- R >= 4.0.0 depends
- Formula * imports
- MASS * imports
- Matrix * imports
- Rdpack >= 0.7 imports
- VGAM * imports
- betareg * imports
- lme4 * imports
- methods * imports
- stats * imports
- utils * imports
- knitr * suggests
- nlraa * suggests
- rmarkdown * suggests
- testthat >= 3.0.0 suggests
.github/workflows/R-CMD-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/pkgdown.yaml
actions
- JamesIves/github-pages-deploy-action v4.4.1 composite
- actions/checkout v3 composite
- r-lib/actions/setup-pandoc v2 composite
- r-lib/actions/setup-r v2 composite
- r-lib/actions/setup-r-dependencies v2 composite