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supcluster (version 1.0.1)

Supervised Cluster Analysis

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.

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Version

Install

install.packages('supcluster')

Monthly Downloads

29

Version

1.0.1

License

GPL-2

Maintainer

David A Schoenfeld

Last Published

May 19th, 2022

Functions in supcluster (1.0.1)

beta.by.gene

Utility to Associate the Value of \(\beta\) with the Feature it is Assocated With
compare.chains

Compare Chains to Test Algorithm Coverage
generate.cluster.data

Function to Generate Data According to the Supcluster Model
supcluster

Clustering of Features Supervised by an Outcome
binaryOutcome

supcluster-package

Supervised Cluster Anaysis
coxLink

Used with supcluster when the outcome data object is a censored survival variable.
gene_names

Trauma Data for Supervised Clustering
concordmap

Calculate the Frequency with which each Pair of Features are in the Same Cluster
binaryLink

Used with supcluster when the outcome data object is binary
survivalOutcome

tab1

Simulates Supcluster Function
trauma_data

Trauma Data for Supervised Clustering