The new version (0.2.0) of rhe 'pivmet' package is released on CRAN: https://CRAN.R-project.org/package=pivmet. The package offers a collection of pivotal algorithms for: relabelling the MCMC chains in order to undo the label switching problem in Bayesian mixture models, as proposed in Egidi et al. (2018a); initializing the centers of the classical k-means algorithm in order to obtain a better clustering solution (Egidi et al., 2018b). The new version incorporates the Stan language for fitting efficient mixture models. github package page at: https://github.com/LeoEgidi/pivmet Here are the two referred articles: Egidi et al. (2018a) https://link.springer.com/article/10.1007/s11222-017-9774-2 Egidi et al. (2018b) https://www.researchgate.net/profile/Leonardo_Egidi/publication/326225330_K-means_seeding_via_MUS_algorithm_-_Inizializzazione_del_K-means_tramite_l%27algoritmo_MUS/links/5b3f2c2caca27207851c7865/K-means-seeding-via-MUS-algorithm-Inizializzazione-del-K-means-tramite-lalgoritmo-MUS.pdf All the best Leonardo Egidi Postdoctoral researcher University of Trieste _______________________________________________ R-packages mailing list r-packa...@r-project.org https://stat.ethz.ch/mailman/listinfo/r-packages ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
