Package: bigIRT 0.1.8

Charles Driver
bigIRT: Fits item response theory models to big data
Fits item response theory models to big data.
Authors:
bigIRT_0.1.8.tar.gz
bigIRT_0.1.8.zip(r-4.7)bigIRT_0.1.8.zip(r-4.6)bigIRT_0.1.8.zip(r-4.5)
bigIRT_0.1.8.tgz(r-4.6-x86_64)bigIRT_0.1.8.tgz(r-4.6-arm64)bigIRT_0.1.8.tgz(r-4.5-x86_64)bigIRT_0.1.8.tgz(r-4.5-arm64)
bigIRT_0.1.8.tar.gz(r-4.7-arm64)bigIRT_0.1.8.tar.gz(r-4.7-x86_64)bigIRT_0.1.8.tar.gz(r-4.6-arm64)bigIRT_0.1.8.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
card.svg |card.png
bigIRT/json (API)
| # Install 'bigIRT' in R: |
| install.packages('bigIRT', repos = c('https://cdriveraus.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/cdriveraus/bigirt/issues
Last updated from:d6072a8ff9. Checks:11 ERROR, 1 OK, 1 FAIL. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | ERROR | 276 | ||
| linux-devel-x86_64 | ERROR | 265 | ||
| source / vignettes | OK | 268 | ||
| linux-release-arm64 | ERROR | 286 | ||
| linux-release-x86_64 | ERROR | 290 | ||
| macos-release-arm64 | ERROR | 219 | ||
| macos-release-x86_64 | ERROR | 425 | ||
| macos-oldrel-arm64 | ERROR | 209 | ||
| macos-oldrel-x86_64 | ERROR | 572 | ||
| windows-devel | ERROR | 455 | ||
| windows-release | ERROR | 297 | ||
| windows-oldrel | ERROR | 328 | ||
| wasm-release | FAIL | 144 |
Exports:dropPerfectScoresfitIRTnormaliseIRTsimIRTwleIRT
Dependencies:abindbackportsBHcallrcheckmateclicpp11data.tabledescdistributionalfarvergenericsggplot2gluegridExtragtableinlineisobandlabelinglifecycleloomagrittrmatrixStatsmizenumDerivpillarpkgbuildpkgconfigposteriorprocessxpsQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelrlangrstanrstantoolsS7scalesStanHeadersstatmodtensorAtibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| The 'bigIRT' package. | bigIRT-package bigIRT |
| Drop subjects and items with all perfect scores | dropPerfectScores |
| Fit a binary Item Response Theory (IRT) model | fitIRT |
| normaliseIRT | normaliseIRT |
| Simulate IRT data | simIRT |
| Compute Weighted Likelihood Estimate (WLE) and Standard Error (SE) | wleIRT |