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supclust  

Supervised Clustering of Predictor Variables Such as Genes
View on CRAN: Click here


Download and install supclust package within the R console
Install from CRAN:
install.packages("supclust")

Install from Github:
library("remotes")
install_github("cran/supclust")

Install by package version:
library("remotes")
install_version("supclust", "1.1-1")



Attach the package and use:
library("supclust")
Maintained by
Martin Maechler
[Scholar Profile | Author Map]
First Published: 2004-01-14
Latest Update: 2021-09-27
Description:
Methodology for supervised grouping aka "clustering" of potentially many predictor variables, such as genes etc, implementing algorithms 'PELORA' and 'WILMA'.
How to cite:
Martin Maechler (2004). supclust: Supervised Clustering of Predictor Variables Such as Genes. R package version 1.1-1, https://cran.r-project.org/web/packages/supclust. Accessed 19 Apr. 2025.
Previous versions and publish date:
1.0-1 (2004-01-14 10:37), 1.0-2 (2004-08-19 20:07), 1.0-3 (2004-11-17 12:44), 1.0-4 (2005-05-10 23:14), 1.0-5.1 (2009-08-21 06:38), 1.0-5 (2005-05-18 17:20), 1.0-6 (2010-09-02 21:49), 1.0-7 (2011-12-02 17:23), 1.1-0 (2020-10-15 18:30)
Other packages that cited supclust R package
View supclust citation profile
Other R packages that supclust depends, imports, suggests or enhances
Complete documentation for supclust
Functions, R codes and Examples using the supclust R package
Some associated functions: back.search . coef.pelora . dlda . fitted.pelora . fitted.wilma . leukemia . margin . pelora . plot.pelora . plot.wilma . predict.pelora . predict.wilma . print.pelora . print.wilma . score . sign.change . signflip . standardize.genes . summary.pelora . summary.wilma . wilma . 
Some associated R codes: pelora-utils.R . pelora.R . wilma-utils.R . wilma.R . zzz.R .  Full supclust package functions and examples
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