Package: emIRT 0.0.14
Kosuke Imai
emIRT: EM Algorithms for Estimating Item Response Theory Models
Various Expectation-Maximization (EM) algorithms are implemented for item response theory (IRT) models. The package includes IRT models for binary and ordinal responses, along with dynamic and hierarchical IRT models with binary responses. The latter two models are fitted using variational EM. The package also includes variational network and text scaling models. The algorithms are described in Imai, Lo, and Olmsted (2016) <doi:10.1017/S000305541600037X>.
Authors:
emIRT_0.0.14.tar.gz
emIRT_0.0.14.tar.gz(r-4.5-noble)emIRT_0.0.14.tar.gz(r-4.4-noble)
emIRT_0.0.14.tgz(r-4.4-emscripten)emIRT_0.0.14.tgz(r-4.3-emscripten)
emIRT.pdf |emIRT.html✨
emIRT/json (API)
| # Install 'emIRT' in R: |
| install.packages('emIRT', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- AsahiTodai - Asahi-Todai Elite Survey
- dwnom - Poole-Rosenthal DW-NOMINATE data and scores, 80-110 U.S. Senate
- manifesto - German Manifesto Data
- mq_data - Martin-Quinn Judicial Ideology Scores
- ustweet - U.S. Twitter Following Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 months agofrom:521131d4a2. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 04 2024 |
| R-4.5-linux-x86_64 | OK | Dec 04 2024 |
Exports:binIRTboot_emIRTconvertRCdynIRTgetStartshierIRTmakePriorsnetworkIRTordIRTpoisIRT
Dependencies:MASSpsclRcppRcppArmadillo
