Software

I have authored or contributed to the following R packages:

• BayesLCA — Bayesian Latent Class Analysis using several different methods
• betaclust — A Family of Beta Mixture Models for Clustering Beta-Valued DNA Methylation Data
• betaHMM — A Hidden Markov Model Approach for Identifying Differentially Methylated Sites and Regions for Beta-Valued DNA Methylation Data
• digeR — An R GUI Tool for Analyzing 2D DIGE Data
• egoTERGM — Estimation of Ego-Temporal Exponential Random Graph Models via Expectation Maximization (EM)
• idiffomix — Integrated Differential Analysis of Multi Omics Data using a Joint Mixture Model
• LCAvarsel — Variable Selection for Latent Class Analysis
• MBCbook — Companion Package for the Book “Model-Based Clustering and Classification for Data Science”
• mclust — Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation
• MEclustnet — Fit the Mixture of Experts Latent Position Cluster Model to Network Data
• MEDseq — Mixtures of Exponential-Distance Models with Covariates
• MetabolSSMF — Simplex-Structured Matrix Factorisation for Metabolomics Analysis
• mixggm — Mixtures of Gaussian Graphical Models
• MoEClust — Gaussian Parsimonious Clustering Models with Covariates and a Noise Component
• pgmm — Parsimonious Gaussian Mixture Models
• spaceNet — Latent Space Models for Multidimensional Networks
• upclass — Updated Classification Methods using Unlabeled Data