Sparse Principal Component Analysis via Random Projections (SPCAvRP)

Documentation for package ‘SPCAvRP’ version 0.1

final_estimator	Computes the leading eigenvector from its support
project_covariance	Projects the sample covariance
select_projection	Selects the best projection
SPCAvRP	Computes the leading eigenvector using the SPCAvRP algorithm
SPCAvRP_parallel	Parallel implementation of the SPCAvRP algorithm
SPCAvRP_ranking	Ranks the variables