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RobustLPA  

Robust Latent Profile Analysis
View on CRAN: Click here


Download and install RobustLPA package within the R console
Install from CRAN:
install.packages("RobustLPA")

Install from Github:
library("remotes")
install_github("cran/RobustLPA")

Install by package version:
library("remotes")
install_version("RobustLPA", "0.1.0")



Attach the package and use:
library("RobustLPA")
Maintained by
Valerio Riccardo Aquila
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-07-05
Latest Update: 2026-07-05
Description:
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>.
How to cite:
Valerio Riccardo Aquila (2026). RobustLPA: Robust Latent Profile Analysis. R package version 0.1.0, https://cran.r-project.org/web/packages/RobustLPA. Accessed 14 Jul. 2026.
Previous versions and publish date:
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Complete documentation for RobustLPA
Functions, R codes and Examples using the RobustLPA R package
Full RobustLPA package functions and examples
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