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Provides a comprehensive toolset for estimating Latent Profile Analysis (LPA) models that are robust to multivariate outliers and missing data. By integrating a high-performance 'C++' engine via 'RcppArmadillo' with a Full Information Maximum Likelihood (FIML) approach and Huber weighting, it reliably extracts latent profiles even in complex datasets. It supports multiple geometric variance-covariance models, along with functions for bootstrapped likelihood ratio tests and plotting. For methodological details on the Bootstrapped Likelihood Ratio Test, see Nylund et al. (2007) <doi:10.1080/10705510701575396>. For robust clustering methods, see Garcia-Escudero et al. (2010) <doi:10.1007/s11634-010-0064-5>.
| Version: | 0.1.0 |
| Imports: | Rcpp, ggplot2, stats |
| LinkingTo: | Rcpp, RcppArmadillo |
| Published: | 2026-07-05 |
| DOI: | 10.32614/CRAN.package.RobustLPA |
| Author: | Valerio Riccardo Aquila
|
| Maintainer: | Valerio Riccardo Aquila <valerio_aquila at hotmail.it> |
| License: | GPL (≥ 3) |
| NeedsCompilation: | yes |
| Materials: | NEWS |
| CRAN checks: | RobustLPA results |
| Reference manual: | RobustLPA.html , RobustLPA.pdf |
| Package source: | RobustLPA_0.1.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: RobustLPA_0.1.0.zip, r-oldrel: RobustLPA_0.1.0.zip |
| macOS binaries: | r-release (arm64): RobustLPA_0.1.0.tgz, r-oldrel (arm64): RobustLPA_0.1.0.tgz, r-release (x86_64): RobustLPA_0.1.0.tgz, r-oldrel (x86_64): RobustLPA_0.1.0.tgz |
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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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