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supcluster  

Supervised Cluster Analysis
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("supcluster", "1.0.1")



Attach the package and use:
library("supcluster")
Maintained by
David A. Schoenfeld
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-05-18
Latest Update:
Description:
Clusters features under the assumption that each cluster has a random effect and there is an outcome variable that is related to the random effects by a linear regression. In this way the cluster analysis is ``supervised'' by the outcome variable. An alternate specification is that features in each cluster have the same compound symmetric normal distribution, and the conditional distribution of the outcome given the features has the same coefficient for each feature in a cluster.
How to cite:
David A. Schoenfeld (2015). supcluster: Supervised Cluster Analysis. R package version 1.0.1, https://cran.r-project.org/web/packages/supcluster. Accessed 25 Jun. 2026.
Previous versions and publish date:
1.0.1 (2022-05-19 16:50), 1.0 (2015-05-18 22:45)
Other packages that cited supcluster R package
View supcluster citation profile
Other R packages that supcluster depends, imports, suggests or enhances
Functions, R codes and Examples using the supcluster R package
Some associated functions: beta.by.gene . binaryLink . binaryOutcome . compare.chains . concordmap . coxLink . gene_names . generate.cluster.data . supcluster-package . supcluster . survivalOutcome . tab1 . trauma_data . 
Some associated R codes: binary_link.R . concordmap.R . generate.cluster.data.R . supcluster.R . tab1.R .  Full supcluster package functions and examples
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