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onlinePCA (version 1.3.1)

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

Install

install.packages('onlinePCA')

Monthly Downloads

170

Version

1.3.1

License

GPL-3

Maintainer

David Degras

Last Published

September 22nd, 2016

Functions in onlinePCA (1.3.1)

ccipca

Candid Covariance-Free Incremental PCA

batchpca

Batch PCA

incRpca.block

Incremental PCA with Block Update

coef2fd

Recover functional data from their B-spline coefficients

incRpca

Incremental PCA

bsoipca

Block Stochastic Orthononal Iteration (BSOI)

impute

BLUP Imputation of Missing Values

create.basis

Create a smooth B-spline basis

ghapca

Generalized Hebbian Algorithm for PCA

fd2coef

Compute the coefficients of functional data in a B-spline basis

perturbationRpca

Recursive PCA using a rank 1 perturbation method

updateMean

Update the Sample Mean Vector

sgapca

Stochastic Gradient Ascent PCA

onlinePCA-package

Online Principal Component Analysis

secularRpca

Recursive PCA Using Secular Equations

updateCovariance

Update the Sample Covariance Matrix

incRpca.rc

Incremental PCA With Reduced Complexity

snlpca

Subspace Network Learning PCA