Package: pgmm 1.2.7

Paul D. McNicholas

pgmm: Parsimonious Gaussian Mixture Models

Carries out model-based clustering or classification using parsimonious Gaussian mixture models. McNicholas and Murphy (2008) <doi:10.1007/s11222-008-9056-0>, McNicholas (2010) <doi:10.1016/j.jspi.2009.11.006>, McNicholas and Murphy (2010) <doi:10.1093/bioinformatics/btq498>, McNicholas et al. (2010) <doi:10.1016/j.csda.2009.02.011>.

Authors:Paul D. McNicholas [aut, cre], Aisha ElSherbiny [aut], K. Raju Jampani [ctb], Aaron F. McDaid [aut], T. Brendan Murphy [aut], Larry Banks [ctb]

pgmm_1.2.7.tar.gz
pgmm_1.2.7.tar.gz(r-4.5-noble)pgmm_1.2.7.tar.gz(r-4.4-noble)
pgmm_1.2.7.tgz(r-4.4-emscripten)pgmm_1.2.7.tgz(r-4.3-emscripten)
pgmm.pdf |pgmm.html
pgmm/json (API)

# Install 'pgmm' in R:
install.packages('pgmm', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
Datasets:

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

openblas

3.00 score 1 stars 2 packages 167 scripts 838 downloads 1 mentions 1 exports 0 dependencies

Last updated 1 years agofrom:0b924642af. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 18 2024
R-4.5-linux-x86_64OKDec 18 2024

Exports:pgmmEM

Dependencies: