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Implements fast, exact bootstrap Principal Component Analysis and Singular Value Decompositions for high dimensional data, as described in <doi:10.1080/01621459.2015.1062383> (see also <doi:10.48550/arXiv.1405.0922> ). For data matrices that are too large to operate on in memory, users can input objects with class 'ff' (see the 'ff' package), where the actual data is stored on disk. In response, this package will implement a block matrix algebra procedure for calculating the principal components (PCs) and bootstrap PCs. Depending on options set by the user, the 'parallel' package can be used to parallelize the calculation of the bootstrap PCs.
Version: | 1.1 |
Depends: | R (≥ 3.0.2) |
Imports: | ff, parallel |
Published: | 2021-02-02 |
DOI: | 10.32614/CRAN.package.bootSVD |
Author: | Aaron Fisher |
Maintainer: | Aaron Fisher <afishe27 at alumni.jh.edu> |
License: | GPL-2 |
URL: | http://arxiv.org/abs/1405.0922 |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | bootSVD results |
Reference manual: | bootSVD.pdf |
Package source: | bootSVD_1.1.tar.gz |
Windows binaries: | r-devel: bootSVD_1.1.zip, r-release: bootSVD_1.1.zip, r-oldrel: bootSVD_1.1.zip |
macOS binaries: | r-release (arm64): bootSVD_1.1.tgz, r-oldrel (arm64): bootSVD_1.1.tgz, r-release (x86_64): bootSVD_1.1.tgz, r-oldrel (x86_64): bootSVD_1.1.tgz |
Old sources: | bootSVD archive |
Reverse imports: | smartsnp |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.