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bootSVD  

Fast, Exact Bootstrap Principal Component Analysis for High Dimensional Data
View on CRAN: Click here


Download and install bootSVD package within the R console
Install from CRAN:
install.packages("bootSVD")

Install from Github:
library("remotes")
install_github("cran/bootSVD")

Install by package version:
library("remotes")
install_version("bootSVD", "1.1")



Attach the package and use:
library("bootSVD")
Maintained by
Aaron Fisher
[Scholar Profile | Author Map]
First Published: 2014-07-21
Latest Update: 2021-02-02
Description:
Implements fast, exact bootstrap Principal Component Analysis and Singular Value Decompositions for high dimensional data, as described in (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.
How to cite:
Aaron Fisher (2014). bootSVD: Fast, Exact Bootstrap Principal Component Analysis for High Dimensional Data. R package version 1.1, https://cran.r-project.org/web/packages/bootSVD. Accessed 03 May. 2025.
Previous versions and publish date:
0.1 (2014-07-21 23:18), 0.2 (2015-04-22 08:05), 0.5 (2015-06-02 00:22)
Other packages that cited bootSVD R package
View bootSVD citation profile
Other R packages that bootSVD depends, imports, suggests or enhances
Complete documentation for bootSVD
Functions, R codes and Examples using the bootSVD R package
Some associated functions: As2Vs . EEG_leadingV . EEG_mu . EEG_score_var . bootPCA . bootSVD . bootSVD_LD . fastSVD . ffmatrixmult . genBootIndeces . genQ . getMomentsAndMomentCI . os . qrSVD . reindexMatricesByK . reindexVectorsByK . simEEG . 
Some associated R codes: bootstrap_functions.R .  Full bootSVD package functions and examples
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