hmcdm

R package for fitting hidden Markov cognitive diagnosis models for learning.

https://github.com/tmsalab/hmcdm

Science Score: 13.0%

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

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CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
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.zenodo.json file
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DOI references
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Academic publication links
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Scientific vocabulary similarity
Low similarity (13.7%) to scientific vocabulary

Keywords

cognitive-diagnostic-models psychometrics r rcpp rcpparmadillo

Last synced: 6 months ago · JSON representation

Repository

R package for fitting hidden Markov cognitive diagnosis models for learning.

Basic Info

Host: GitHub
Owner: tmsalab
Language: C++
Default Branch: master
Homepage: https://tmsalab.github.io/hmcdm
Size: 22.9 MB

Statistics

Stars: 8
Watchers: 1
Forks: 7
Open Issues: 0
Releases: 7

Topics

cognitive-diagnostic-models psychometrics r rcpp rcpparmadillo

Created almost 8 years ago · Last pushed almost 3 years ago

Metadata Files

Readme Changelog

README.Rmd

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# hmcdm


[![R-CMD-check](https://github.com/tmsalab/hmcdm/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/tmsalab/hmcdm/actions/workflows/R-CMD-check.yaml)
[![Package-License](http://img.shields.io/badge/license-GPL%20(%3E=2)-brightgreen.svg?style=flat)](http://www.gnu.org/licenses/gpl-2.0.html)


The goal of `hmcdm` is to provide an implementation of Hidden Markov Cognitive Diagnosis Models for Learning.

## Installation

You can install `hmcdm` from CRAN using:

```{r cran-installation, eval = FALSE}
install.packages("hmcdm")
```

Or, you can be on the cutting-edge development version on GitHub using:

```{r gh-installation, eval = FALSE}
if(!requireNamespace("remotes")) install.packages("remotes")
remotes::install_github("tmsalab/hmcdm")
```

## Usage

To use `hmcdm`, load the package using:

```{r example, eval = FALSE}
library("hmcdm")
```

## Authors

Susu Zhang, Shiyu Wang, Yinghan Chen, and Sunbeom Kwon

## Citing the hmcdm package

To ensure future development of the package, please cite `hmcdm`
package if used during an analysis or simulation study. Citation information
for the package may be acquired by using in *R*:

```{r, eval = FALSE}
citation("hmcdm")
```

## License

GPL (>= 2)

Owner

Name: TMSA Lab @ UIUC
Login: tmsalab
Kind: organization

Repositories: 24
Profile: https://github.com/tmsalab

Testing Measurement and Statistical Analysis Lab at the University of Illinois (UIUC)

GitHub Events

Total

Watch event: 1

Last Year

Watch event: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 1
Total pull requests: 3
Average time to close issues: about 14 hours
Average time to close pull requests: 10 minutes
Total issue authors: 1
Total pull request authors: 2
Average comments per issue: 0.0
Average comments per pull request: 0.67
Merged pull requests: 2
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

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Top Authors

Issue Authors

coatless (1)

Pull Request Authors

coatless (2)
JiajunX (1)

Top Labels

Issue Labels

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Packages

Total packages: 1
Total downloads:
- cran 268 last-month

Total dependent packages: 0
Total dependent repositories: 0
Total versions: 3
Total maintainers: 1

cran.r-project.org: hmcdm

Hidden Markov Cognitive Diagnosis Models for Learning

Homepage: https://github.com/tmsalab/hmcdm
Documentation: http://cran.r-project.org/web/packages/hmcdm/hmcdm.pdf
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Latest release: 2.1.1
published almost 3 years ago

Versions: 3
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 268 Last month

Rankings

Forks count: 9.1%

Stargazers count: 22.5%

Dependent packages count: 29.8%

Average: 30.6%

Dependent repos count: 35.5%

Downloads: 56.4%

Maintainers (1)

sunbeom2@illinois.edu