_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-varsellcm 2.1.3.2
Propagated dependencies: r-shiny@1.11.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-mgcv@1.9-4 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/v.scm (guix-cran packages v)
Home page: http://varsellcm.r-forge.r-project.org/
Licenses: GPL 2+
Synopsis: Variable Selection for Model-Based Clustering of Mixed-Type Data Set with Missing Values
Description:

Full model selection (detection of the relevant features and estimation of the number of clusters) for model-based clustering (see reference here <doi:10.1007/s11222-016-9670-1>). Data to analyze can be continuous, categorical, integer or mixed. Moreover, missing values can occur and do not necessitate any pre-processing. Shiny application permits an easy interpretation of the results.

Total results: 1