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'.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0 |
rolling linux/jammy R-4.5 | DLCA_1.0.tar.gz |
305.9 KiB |
1.0 |
rolling linux/noble R-4.5 | DLCA_1.0.tar.gz |
314.7 KiB |
1.0 |
rolling source/ R- | DLCA_1.0.tar.gz |
65.9 KiB |
1.0 |
latest linux/jammy R-4.5 | DLCA_1.0.tar.gz |
305.9 KiB |
1.0 |
latest linux/noble R-4.5 | DLCA_1.0.tar.gz |
314.7 KiB |
1.0 |
latest source/ R- | DLCA_1.0.tar.gz |
65.9 KiB |
1.0 |
2026-04-23 source/ R- | DLCA_1.0.tar.gz |
0 B |