Contains some procedures for latent variable modelling with a
particular focus on multilevel data.
The 'LAM' package contains mean and covariance structure modelling
for multivariate normally distributed data (mlnormal()),
a general Metropolis-Hastings algorithm (amh()) and penalized
maximum likelihood estimation (pmle()).
| Version: |
0.2-9 |
| Depends: |
R (≥ 3.1) |
| Imports: |
CDM, coda, graphics, Rcpp, sirt (≥ 2.0), stats, TAM (≥ 2.8), utils |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
lavaan, lme4, MASS, STARTS (≥ 0.2) |
| Published: |
2018-03-20 |
| Author: |
Alexander Robitzsch [aut,cre] |
| Maintainer: |
Alexander Robitzsch <robitzsch at ipn.uni-kiel.de> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
https://github.com/alexanderrobitzsch/LAM |
| NeedsCompilation: |
yes |
| Citation: |
LAM citation info |
| Materials: |
README NEWS |
| CRAN checks: |
LAM results |