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DLCA: Divisive Latent Class Analysis

Provides algorithms for estimating divisive and standard latent class models. The divisive latent class method follows van der Palm, van der Ark and Vermunt (2016) <doi:10.1007/s00357-016-9195-5>. Both algorithms use expectation-maximization and Newton-Raphson optimization and are implemented in 'C++' for speed through 'Rcpp'.

Version: 1.0
Imports: Rcpp (≥ 0.11.4)
LinkingTo: Rcpp
Published: 2026-08-07
DOI: 10.32614/CRAN.package.DLCA
Author: Daniel W. van der Palm [aut, cre], L. Andries van der Ark [ctb]
Maintainer: Daniel W. van der Palm <danielvdpalm at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
SystemRequirements: OpenMP
CRAN checks: DLCA results [issues need fixing before 2026-08-21]

Documentation:

Reference manual: DLCA.html , DLCA.pdf

Downloads:

Package source: DLCA_1.0.tar.gz
Windows binaries: r-devel: DLCA_1.0.zip, r-release: DLCA_1.0.zip, r-oldrel: DLCA_1.0.zip
macOS binaries: r-release (arm64): DLCA_1.0.tgz, r-oldrel (arm64): DLCA_1.0.tgz, r-release (x86_64): DLCA_1.0.tgz, r-oldrel (x86_64): DLCA_1.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=DLCA to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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