HighDimenCDM: Stochastic EM Algorithm for High-Dimensional Cognitive Diagnosis Models

Provides stochastic expectation-maximization (stEM) algorithms for estimating high-dimensional cognitive diagnosis models. The package implements stochastic EM algorithms for cognitive diagnosis models with a large number of attributes. It includes estimation functions and example datasets for model fitting and analysis. The methods are described in Ma, W., Wang, K., and Xu, G. (Accepted). "Parameter estimation of cognitive diagnosis models with stochastic EM algorithm." Behaviometrika.

Version:	0.1.0
Depends:	R (≥ 3.5)
Imports:	coda, GDINA, Rcpp (≥ 0.12.1)
LinkingTo:	Rcpp, RcppArmadillo
Published:	2026-07-24
DOI:	10.32614/CRAN.package.HighDimenCDM (may not be active yet)
Author:	Yuxuan Mei [aut, cre], Wenchao Ma [aut], Kevin Wang [aut], Gongjun Xu [aut]
Maintainer:	Yuxuan Mei <mei00060 at umn.edu>
License:	GPL-3
NeedsCompilation:	yes
Materials:	README
CRAN checks:	HighDimenCDM results

Documentation:

Reference manual:

HighDimenCDM.html , HighDimenCDM.pdf

Downloads:

Package source:	HighDimenCDM_0.1.0.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries:	r-release (arm64): HighDimenCDM_0.1.0.tgz, r-oldrel (arm64): HighDimenCDM_0.1.0.tgz, r-release (x86_64): HighDimenCDM_0.1.0.tgz, r-oldrel (x86_64): HighDimenCDM_0.1.0.tgz

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