Who Cited It

mclust 5: Clustering, Classification and Density Estimation Using Gaussian Finite Mixture Models

2016 · The R Journal · 3,074 citations · 1 from inside this corpus

Luca Scrucca, Michael Fop, Thomas Brendan Murphy

Finite mixture models are being used increasingly to model a wide variety of random phenomena for clustering, classification and density estimation. mclust is a powerful and popular package which allows modelling of data as a Gaussian finite mixture with different covariance structures and different numbers of mixture components, for a variety of purposes of analysis. Recently, version 5 of the package has been made available on CRAN. This updated version adds new covariance structures, dimension reduction capabilities for visualisation, model selection criteria, initialisation strategies for the EM algorithm, and bootstrap-based inference, making it a full-featured R package for data analysis via finite mixture modelling.

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What this paper cites, inside the corpus

What cites it, inside the corpus

PaperYearCited
Finite Mixture Models20007,427

Topics

Bayesian Methods and Mixture ModelsComputer Science
Algorithms and Data CompressionComputer Science
Advanced Clustering Algorithms ResearchComputer Science

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complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports3 author record(s) attached.
  • supports72 reference(s) recorded.
  • supportsThe DOI's year agrees with the publication year.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:47+00:00.

sha256 a08467ae9504f237…