CCtestr provides a hypothesis testing framework for cluster validation. Using a modified consensus clustering algorithm, PAC scores are calculated for data simulated from an input matrix in order to estimate the theoretical null distribution of each cluster number k's performance metrics. Results for real data are subsequently evaluated relative to these distributions. By systematically testing against wellformulated null hypotheses, test statistics and pvalues are computed with high accuracy and known precision.
Package details 


Maintainer  
License  GPL (>= 3) 
Version  0.0.0.9000 
Package repository  View on GitHub 
Installation 
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