Covariance matrix filtering with bootstrapped hierarchies

@article{Bongiorno2021CovarianceMF,
  title={Covariance matrix filtering with bootstrapped hierarchies},
  author={Christian Bongiorno and Damien Challet},
  journal={PLoS ONE},
  year={2021},
  volume={16}
}
Cleaning covariance matrices is a highly non-trivial problem, yet of central importance in the statistical inference of dependence between objects. We propose here a probabilistic hierarchical clustering method, named Bootstrapped Average Hierarchical Clustering (BAHC), that is particularly effective in the high-dimensional case, i.e., when there are more objects than features. When applied to DNA microarray, our method yields distinct hierarchical structures that cannot be accounted for by… 
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