# ------------------------------------------------ # CITATION.cff file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # ------------------------------------------------ cff-version: 1.2.0 message: 'To cite package "RobustLPA" in publications use:' type: software license: GPL-3.0-or-later title: 'RobustLPA: Robust Latent Profile Analysis' version: 0.1.0 abstract: 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) . For robust clustering methods, see Garcia-Escudero et al. (2010) . authors: - family-names: Aquila given-names: Valerio Riccardo email: valerio_aquila@hotmail.it orcid: https://orcid.org/0009-0004-2231-2141 repository: https://vraquila.r-universe.dev commit: 7820b7e18570355cb291456c9a5f83f4d5a3f130 date-released: '2026-07-05' contact: - family-names: Aquila given-names: Valerio Riccardo email: valerio_aquila@hotmail.it orcid: https://orcid.org/0009-0004-2231-2141