Package: dina 2.0.0.900

James Joseph Balamuta

dina: Bayesian Estimation of DINA Model

Estimate the Deterministic Input, Noisy "And" Gate (DINA) cognitive diagnostic model parameters using the Gibbs sampler described by Culpepper (2015) <doi:10.3102/1076998615595403>.

Authors:Steven Andrew Culpepper [aut, cph], James Joseph Balamuta [aut, cre]

dina_2.0.0.900.tar.gz
dina_2.0.0.900.zip(r-4.5)dina_2.0.0.900.zip(r-4.4)dina_2.0.0.900.zip(r-4.3)
dina_2.0.0.900.tgz(r-4.4-x86_64)dina_2.0.0.900.tgz(r-4.4-arm64)dina_2.0.0.900.tgz(r-4.3-x86_64)dina_2.0.0.900.tgz(r-4.3-arm64)
dina_2.0.0.900.tar.gz(r-4.5-noble)dina_2.0.0.900.tar.gz(r-4.4-noble)
dina_2.0.0.900.tgz(r-4.4-emscripten)dina_2.0.0.900.tgz(r-4.3-emscripten)
dina.pdf |dina.html✨
dina/json (API)
NEWS

# Install 'dina' in R:
install.packages('dina', repos = c('https://tmsalab.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/tmsalab/dina/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

armadillobayesiangibbs-samplerirtitem-response-theorypsychometricsrcpprcpparmadillo

3.85 score 14 stars 3 scripts 274 downloads 2 exports 4 dependencies

Last updated 5 years agofrom:1567f87b5a. Checks:OK: 1 NOTE: 8. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 06 2024
R-4.5-win-x86_64NOTENov 06 2024
R-4.5-linux-x86_64NOTENov 06 2024
R-4.4-win-x86_64NOTENov 06 2024
R-4.4-mac-x86_64NOTENov 06 2024
R-4.4-mac-aarch64NOTENov 06 2024
R-4.3-win-x86_64NOTENov 06 2024
R-4.3-mac-x86_64NOTENov 06 2024
R-4.3-mac-aarch64NOTENov 06 2024

Exports:dinaDINA_Gibbs

Dependencies:RcppRcppArmadillorgensimcdm