mixtools
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Tools for Analyzing Finite Mixture Models
mixtools: Tools for Analyzing Finite Mixture Models ![](https://github.com/dsy109/mixtools/raw/master/man/figures/mixtools.png)
Synopsis
The mixtools package provides functions for analyzing finite mixture models. Parametric and semiparametric mixture models are handled. Various tools are include for determining the number of components. Visualizations include histograms with the estimated mixture model overlaid, 2D and 3D scatterplots for relevant mixture fits, and the mixturegram. More details about the package are included in both the original JSS article as well as a technical report on the open archive HAL.
Other highlights:
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Includes estimation of various parametric and semiparametric mixtures-of-regressions models.
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Functions to help with determining the number of components, including bootstrapping the likelihood ratio test statistic, mixturegrams, and model selection criteria.
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Functions available for estimating Reliability Mixture Models (RMMs).
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Includes a Metropolis-Hastings algorithm for estimating a mixture-of-linear-regressions model.
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Includes some real datasets for which mixture models have been shown to provide good fits.
Documentation
The JSS article and the technical report on HAL both provide documentation about the mixtools package. Moreover, the help file also documents the references used for each function.
Examples
Additional examples for the mixtools package are currently being developed for a Shiny app.
Installation
Released and tested versions of mixtools are available via the CRAN network, and can be installed from within R via
install.packages("mixtools")
Support
The issue tickets at the GitHub repo are the primary bug reporting interface. As with the other web resources, previous issues can be searched as well.
Authors
Derek S. Young, Tatiana Benaglia, Didier Chauveau, David Hunter, Kedai Cheng, Ryan Elmore, Thomas Hettmansperger, Hoben Thomas, Fengjuan Xua
License
GPL (>= 2)
Funding Acknowledgment
This package is based upon work supported by the National Science Foundation, Grant Number SES-0518772 and the Chan Zuckerberg Initiative, Grant Number 2020-225193.
Code of Conduct
As contributors and maintainers of this project, we pledge to respect all people who contribute through reporting issues, posting feature requests, updating documentation, submitting pull requests or patches, and other activities. Both contributors and maintainers must consistently demonstrate acceptable behavior, respectful communications, and professional conduct. Project maintainers have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this Code of Conduct. Project maintainers who do not follow the Code of Conduct may be removed from the project team. Instances of abusive, harassing, or otherwise unacceptable behavior may be reported by opening an issue or contacting one or more of the project maintainers. By contributing to this project, you agree to abide by its terms.
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