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onlinePCA (version 1.3.2)
Online Principal Component Analysis
Description
Online PCA for multivariate and functional data using perturbation methods, low-rank incremental methods, and stochastic optimization methods.
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Version
1.3.2
1.3.1
1.3
1.2
1.0-1
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Install
install.packages('onlinePCA')
Monthly Downloads
217
Version
1.3.2
License
GPL-3
Maintainer
David Degras
Last Published
November 15th, 2023
Functions in onlinePCA (1.3.2)
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updateCovariance
Update the Sample Covariance Matrix
snlpca
Subspace Network Learning PCA
incRpca.rc
Incremental PCA With Reduced Complexity
perturbationRpca
Recursive PCA using a rank 1 perturbation method
sgapca
Stochastic Gradient Ascent PCA
updateMean
Update the Sample Mean Vector
onlinePCA-package
Online Principal Component Analysis
secularRpca
Recursive PCA Using Secular Equations
incRpca
Incremental PCA
ghapca
Generalized Hebbian Algorithm for PCA
fd2coef
Compute the coefficients of functional data in a B-spline basis
bsoipca
Block Stochastic Orthononal Iteration (BSOI)
incRpca.block
Incremental PCA with Block Update
coef2fd
Recover functional data from their B-spline coefficients
ccipca
Candid Covariance-Free Incremental PCA
create.basis
Create a smooth B-spline basis
batchpca
Batch PCA
impute
BLUP Imputation of Missing Values