Science Score: 23.0%
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
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○DOI references
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✓Academic publication links
Links to: nature.com -
○Committers with academic emails
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○Scientific vocabulary similarity
Low similarity (14.3%) to scientific vocabulary
Keywords
elo
elo-rating
maximum-likelihood-estimation
Last synced: 6 months ago
·
JSON representation
Repository
Maximum-likelihood fitting of Elo scores
Basic Info
- Host: GitHub
- Owner: jtfeld
- Language: R
- Default Branch: master
- Homepage: https://jtfeld.github.io/EloOptimized/
- Size: 8.81 MB
Statistics
- Stars: 3
- Watchers: 0
- Forks: 1
- Open Issues: 0
- Releases: 2
Topics
elo
elo-rating
maximum-likelihood-estimation
Created over 7 years ago
· Last pushed almost 2 years ago
Metadata Files
Readme
README.Rmd
---
output: github_document
---
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "README-"
)
```
```{r,echo = FALSE}
library(EloOptimized)
```
# EloOptimized
[](https://github.com/jtfeld/EloOptimized/actions/workflows/R-CMD-check.yaml)
[](https://cran.r-project.org/package=EloOptimized)
[](https://cran.r-project.org/package=EloOptimized)
[Package website](https://jtfeld.github.io/EloOptimized/)
EloOptimized provides tools to implement the maximum likelihood methods for deriving Elo scores as published in [Foerster, Franz et al. (2016). Chimpanzee females queue but males compete for social status](https://www.nature.com/articles/srep35404). In addition, it provides functionality to efficiently generate traditional Elo scores using a simplified procedure that doesn't require the use of cumbersome presence matrices. Finally, it quickly generates a number of additional Elo-based indices (ordinal, normalized, cardinal, and categorical ranks and rank scores) of potential use to researchers, as outlined in the linked manuscript.
## Installation
```{r gh-installation, eval = FALSE}
# Current version on Github:
# install.packages("devtools")
devtools::install_github("jtfeld/EloOptimized")
# CRAN-approved version on CRAN:
install.packages("EloOptimized")
```
## Example
There are two functions of interest. Use eloratingopt() to calculate Elo scores using optimized Elo parameter values, or eloratingfixed() to calculate Elo scores using user-defined parameter values.
```{r example, eval = FALSE}
# to generate Elo scores using fixed initial Elo scores (1000) and a ML-fitted value for the K parameter:
nbaelo = eloratingopt(agon_data = nba, fit_init_elo = FALSE)
# to generate Elo scores using fixed default initial Elo scores and default K:
nbaelo = eloratingfixed(agon_data = nba, k = 100, init_elo = 1000)
```
To recreate the results from the 2016 manuscript, use the following code:
```{r MS example, eval = FALSE}
# Males, model type 1:
melo1 = eloratingopt(agon_data = chimpagg_m, pres_data = chimppres_m, fit_init_elo = F)
# Males, model type 3:
melo3 = eloratingopt(agon_data = chimpagg_m[101:nrow(chimpagg_m),],
pres_data = chimppres_m, fit_init_elo = T)
# Females, model type 1:
felo1 = eloratingopt(agon_data = chimpagg_f, pres_data = chimppres_f, fit_init_elo = F)
# Females, model type 3:
felo3 = eloratingopt(agon_data = chimpagg_f[101:nrow(chimpagg_f),],
pres_data = chimppres_f, fit_init_elo = T)
```
Owner
- Name: Joseph T Feldblum, Ph.D.
- Login: jtfeld
- Kind: user
- Location: Durham, NC
- Company: Duke University
- Repositories: 2
- Profile: https://github.com/jtfeld
GitHub Events
Total
Last Year
Committers
Last synced: over 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| jtfeld | j****m@g****m | 86 |
| Steffen Foerster | s****1@g****m | 2 |
| steffenfoerster | s****r | 1 |
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 3
- Total pull requests: 0
- Average time to close issues: 4 months
- Average time to close pull requests: N/A
- Total issue authors: 3
- Total pull request authors: 0
- Average comments per issue: 1.0
- 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
- Dhiordan (1)
- mpentrack (1)
- ioannis12 (1)
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- cran 271 last-month
- Total docker downloads: 41,971
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 3
- Total maintainers: 1
cran.r-project.org: EloOptimized
Optimized Elo Rating Method for Obtaining Dominance Ranks
- Homepage: https://github.com/jtfeld/EloOptimized
- Documentation: http://cran.r-project.org/web/packages/EloOptimized/EloOptimized.pdf
- License: GPL-3
-
Latest release: 0.3.2
published almost 2 years ago
Rankings
Forks count: 28.8%
Dependent packages count: 29.8%
Stargazers count: 35.2%
Dependent repos count: 35.5%
Average: 36.2%
Downloads: 51.7%
Maintainers (1)
Last synced:
6 months ago
Dependencies
DESCRIPTION
cran
- R >= 3.3.0 depends
- BAMMtools * imports
- dplyr * imports
- lubridate * imports
- magrittr * imports
- reshape2 * imports
- rlang * imports
- ggplot2 * suggests
- knitr * suggests
- rmarkdown * 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