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Efficient procedures for fitting the DDPCA (Ke et al., 2019, <arXiv:1906.00051>) by decomposing a large covariance matrix into a lowrank matrix plus a diagonally dominant matrix. The implementation of DDPCA includes the convex approach using the Alternating Direction Method of Multipliers (ADMM) and the nonconvex approach using the iterative projection algorithm. Applications of DDPCA to large covariance matrix estimation and global multiple testing are also included in this package.
Package details 


Author  Tracy Ke [aut], Lingzhou Xue [aut], Fan Yang [aut, cre] 
Maintainer  Fan Yang <fyang1@uchicago.edu> 
License  GPL2 
Version  1.1 
Package repository  View on CRAN 
Installation 
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