Tools for Analyzing Finite Mixture Models
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Updated
Jun 17, 2024 - R
Tools for Analyzing Finite Mixture Models
An R package for clustering longitudinal datasets in a standardized way, providing interfaces to various R packages for longitudinal clustering, and facilitating the rapid implementation and evaluation of new methods
R Package With Shiny App to Perform and Visualize Clustering of Data via Mixtures of Multivariate Gaussian Model
R Package to Perform Clustering of Three-way Count Data Using Mixtures of Matrix Variate Poisson-log Normal Model With Parameter Estimation via MCMC-EM, Variational Gaussian Approximations, or a Hybrid Approach Combining Both.
Model-based clustering with vine copulas
R Package That Can Simultaneously Perform Factor Analysis And Cluster Analysis Of Count Data Via Parsimonious Finite Mixtures of Multivariate Poisson-Log Normal Factor Analyzers. This Model Permits For Parsimonious Covariance Structures And Dimension Reduction, Thus Reducing The Number Of Free Parameters To Be Calculated.
Tidy Tools for Visualizing Mixture Models
Mixture of networks for clustering categorical data
R package for clustering continuous and categorical data, using mixture models.
Functional Latent datA Models for clusterING heterogeneOus curveS
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