HSSVD-package: Biclustering with heterogeneous variance

In HSSVD: Biclustering with Heterogeneous Variance

Description

HSSVD is a recently developed data mining tool for discovering subgroups of patients and genes which simultaneously display unusual levels of variability compared to other genes and patients. Previous biclustering methods were restricted to mean level detection, while the new method can detect both mean and variance biclusters.

Details

Package:	HSSVD
Type:	Package
Version:	1.1
Date:	2014-07-21
License:	GPL-2

low_rank is the full implementation of the HSSVD framework.

Author(s)

Authors: Guanhua Chen and Michael R. Kosorok.
Contributor: Shannon T. Holloway <[e-mail]>
Maintainer: Guanhua Chen <[e-mail]>

References

Chen G, Sullivan PF, Kosorok MR. "Biclustering with heterogeneous variance." Proc. Natl. Acad. Sci. U.S.A.. 2013;110(30):12253-8.

Owen AB, Perry PO (2009) Bi-cross-validation of the SVD and the nonnegative matrix factorization. The Annals of Applied Statistics 3:564-594.

Yang D, Zongming M, Buja, A. "A Sparse SVD Method for High-dimensional Data." arXiv:11112.24333 (2011).

HSSVD documentation built on May 2, 2019, 4:24 a.m.