Package: sparsepca
Type: Package
Title: Sparse Principal Component Analysis (SPCA)
Version: 0.1.0
Author: N. Benjamin Erichson, Peng Zheng, and Sasha Aravkin
Maintainer: N. Benjamin Erichson <erichson@uw.edu>
Description: Sparse principal component analysis (SPCA) attempts to
        find sparse weight vectors (loadings), i.e., a weight vector
        with only a few 'active' (nonzero) values. This approach
        provides better interpretability for the principal components
        in high-dimensional data settings. This is, because the
        principal components are formed as a linear combination of only
        a few of the original variables. This package provides
        efficient routines to compute SPCA. Specifically, a variable
        projection solver is used to compute the sparse solution. In
        addition, a fast randomized accelerated SPCA routine and a
        robust SPCA routine is provided. Robust SPCA allows to capture
        grossly corrupted entries in the data.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/erichson/spca
BugReports: https://github.com/erichson/spca/issues
Imports: rsvd
RoxygenNote: 6.0.1
Repository: https://erichson.r-universe.dev
Date/Publication: 2018-04-07 20:15:00 UTC
RemoteUrl: https://github.com/erichson/spca
RemoteRef: HEAD
RemoteSha: fa896289a68801a4798f53948ff6c2b8f7c54e1c
NeedsCompilation: no
Packaged: 2026-06-21 10:14:37 UTC; root