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dpGMM: Dynamic Programming Based Gaussian Mixture Modelling Tool for 1D and 2D Data

Gaussian mixture modeling of one- and two-dimensional data, provided in original or binned form, with an option to estimate the number of model components. The method uses Gaussian Mixture Models (GMM) with initial parameters determined by a dynamic programming algorithm, leading to stable and reproducible model fitting.

Version: 0.2.2
Depends: R (≥ 3.5), ggplot2, RColorBrewer, stats, pracma
Imports: grDevices, ggpubr, Matrix, reshape2, graphics, methods, mvtnorm
Published: 2026-01-15
DOI: 10.32614/CRAN.package.dpGMM (may not be active yet)
Author: Michal Marczyk [aut, ctb], Kamila Szumala [aut, cre], Joanna Zyla [aut, ctb]
Maintainer: Kamila Szumala <kamila.szumala at polsl.pl>
License: GPL-3
NeedsCompilation: no
Materials: README
CRAN checks: dpGMM results

Documentation:

Reference manual: dpGMM.html , dpGMM.pdf

Downloads:

Package source: dpGMM_0.2.2.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): dpGMM_0.2.2.tgz, r-oldrel (arm64): dpGMM_0.2.2.tgz, r-release (x86_64): dpGMM_0.2.2.tgz, r-oldrel (x86_64): dpGMM_0.2.2.tgz

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.