update.i_pca: Updates a Principal Component Analysis solution

In idm: Incremental Decomposition Methods

Updates a Principal Component Analysis solution

Description

This function updates the Principal Component Analysis (PCA) solution on the covariance matrix using the incremental method of Hall, Marshall & Martin (2002)

Usage

## S3 method for class 'i_pca'
update(object, incdata, current_rank, ...)

Arguments

object	object of class 'i_pca'
incdata	matrix of incoming data
current_rank	Rank of approximation or number of components to compute; if empty, the full rank is used
...	Further arguments passed to update

Value

rowpcoord	Row scores on the principal components
colpcoord	Variable loadings
eg	A list describing the eigenspace of a data matrix, with components u Left eigenvectors v Right eigenvectors m Number of cases d Eigenvalues orgn Data mean
inertia.e	Percentages of explained variance
sv	Singular values
levelnames	Variable names
rowcor	Row squared correlations
rowctr	Row contributions
colcor	Column squared correlations
colctr	Column contributions

References

Hall, P., Marshall, D., & Martin, R. (2002). Adding and subtracting eigenspaces with eigenvalue decomposition and singular value decomposition. Image and Vision Computing, 20(13), 1009-1016.

Iodice D' Enza, A., & Markos, A. (2015). Low-dimensional tracking of association structures in categorical data, Statistics and Computing, 25(5), 1009–1022.

Iodice D'Enza, A., Markos, A., & Buttarazzi, D. (2018). The idm Package: Incremental Decomposition Methods in R. Journal of Statistical Software, Code Snippets, 86(4), 1–24. DOI: 10.18637/jss.v086.c04.

See Also

update.i_mca, i_pca, i_mca, add_es

Examples

data(segmentationData, package = "caret")
HCS = data.frame(scale(segmentationData[,-c(1:3)]))
names(HCS) = abbreviate(names(HCS), minlength = 5)
res_PCA = i_pca(HCS[1:200, ])
aa = seq(from = 201, to = nrow(HCS), by = 200)
aa[length(aa)] = nrow(HCS)+1
for (k in c(1:(length(aa)-1))){
     res_PCA = update(res_PCA, HCS[c((aa[k]):(aa[k+1]-1)),])
    }
#Static plot
plot(res_PCA, animation = FALSE)

idm documentation built on July 12, 2022, 1:05 a.m.