Package: dpGMM 1.0.0

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. For more details see Zyla, J., Szumala, K., Polanski, A., Polanska, J., & Marczyk, M. (2026) <doi:10.1016/j.jocs.2026.102811>.

Authors:Michal Marczyk [aut, ctb], Kamila Szumala [aut, cre], Joanna Zyla [aut, ctb]

dpGMM_1.0.0.tar.gz
dpGMM_1.0.0.zip(r-4.7-any)dpGMM_1.0.0.zip(r-4.6-any)dpGMM_1.0.0.zip(r-4.5-any)
dpGMM_1.0.0.tgz(r-4.6-any)dpGMM_1.0.0.tgz(r-4.5-any)
dpGMM_1.0.0.tar.gz(r-4.7-any)dpGMM_1.0.0.tar.gz(r-4.6-any)
dpGMM_1.0.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
dpGMM/json (API)

# Install 'dpGMM' in R:
install.packages('dpGMM', repos = c('https://szumx123.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • binned - Data example of binned problem in mass spectrometry
  • example - Data of 1D mixed-normal distributions
  • example2D - Data of 2D mixed-normal distributions

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.00 score 4 scripts 258 downloads 19 exports 80 dependencies

Last updated from:d5a1e8dfb6. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK158
source / vignettesOK363
linux-releaseOK302
macos-releaseOK237
macos-oldrelOK224
windows-develOK98
windows-releaseOK351
windows-oldrelOK85
wasm-releaseOK209

Exports:EM_iterEM_iter_2Dfind_class_2Dfind_thr_by_distfind_thr_by_paramsgaussian_mixture_2Dgaussian_mixture_vectorgenerate_distgenerate_dset2Dgenerate_norm1Dgenerate_norm2DGMM_1D_optsGMM_2D_optsplot_gmm_1Dplot_gmm_2D_binnedplot_gmm_2D_origplot_QQplotrunGMMrunGMM2D

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecorrplotcowplotcpp11DerivdoBydplyrfarverforecastFormulafracdiffgenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtableisobandlabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvminqamodelrmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigplyrpolynompracmapurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasreshape2rlangrstatixS7scalesSparseMstringistringrsurvivaltibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrzoo