An R package implementing *Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation*.

Gaussian finite mixture models fitted via EM algorithm for model-based clustering, classification, and density estimation, including Bayesian regularization, dimension reduction for visualization, and resampling-based inference.

## Installation

You can install the released version of **mclust** from CRAN using:

`install.packages("mclust")`

## Usage

Usage of the main functions and several examples are included in the papers shown in the references section below.

For an intro see the vignette **A quick tour of mclust**, which is available as

`vignette("mclust")`

The vignette is also available in the *Vignette* section on the navigation bar on top of the package’s web page.

## References

Scrucca L., Fraley C., Murphy T. B. and Raftery A. E. (2023) *Model-Based Clustering, Classification, and Density Estimation Using mclust in R*. Chapman & Hall/CRC, ISBN: 978-1032234953, https://mclust-org.github.io/book/

Scrucca L., Fop M., Murphy T. B. and Raftery A. E. (2016) mclust 5: clustering, classification and density estimation using Gaussian finite mixture models, *The R Journal*, 8/1, pp. 205-233.

Fraley C. and Raftery A. E. (2002) Model-based clustering, discriminant analysis and density estimation, *Journal of the American Statistical Association*, 97/458, pp. 611-631.