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bootSVD

Fast, Exact Bootstrap Principal Component Analysis for High Dimensional Data

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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 ). 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.

arxiv.org/abs/1405.0922

Key Metrics

Version 1.1
R ≥ 3.0.2
Published 2021-02-02 1183 days ago
Needs compilation? no
License GPL-2
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Maintainer

Maintainer

Aaron Fisher

afishe27@alumni.jh.edu

Authors

Aaron Fisher

Material

README
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

bootSVD archive

Depends

R ≥ 3.0.2

Imports

ff
parallel

Reverse Imports

smartsnp