R package label.switching: Relabelling MCMC Outputs of Mixture Models. The Bayesian estimation of mixture models (and more general hidden Markov models) suffers from the label switching phenomenon, making the MCMC output non-identifiable. This package can be used in order to deal with this problem using various relabelling algorithms.
Keywords for this software
References in zbMATH (referenced in 7 articles )
Showing results 1 to 7 of 7.
- Egidi, Leonardo; Pappadà, Roberta; Pauli, Francesco; Torelli, Nicola: Relabelling in Bayesian mixture models by pivotal units (2018)
- Mollica, Cristina; Tardella, Luca: Bayesian Plackett-Luce mixture models for partially ranked data (2017)
- Saptarshi Chakraborty, Samuel W.K. Wong: BAMBI: An R package for Fitting Bivariate Angular Mixture Models (2017) arXiv
- Cristina Mollica, Luca Tardella: PLMIX: An R package for modeling and clustering partially ranked data (2016) arXiv
- Lee, Jeong Eun; Robert, Christian P.: Importance sampling schemes for evidence approximation in mixture models (2016)
- Okada, Kensuke; Lee, Michael D.: A Bayesian approach to modeling group and individual differences in multidimensional scaling (2016)
- Panagiotis Papastamoulis, Magnus Rattray: BayesBinMix: an R Package for Model Based Clustering of Multivariate Binary Data (2016) arXiv