OADP projection
Online Augmentation, Decomposition, and Procrustes (OADP) projection of
PC loadings onto some study data X.
pca_OADP_proj(X, loadings, sval) pca_OADP_proj2(XV, X_norm, sval)
X |
Data to get PC loadings into. |
loadings |
PC loadings of the reference PCA to project. |
sval |
Singular values of the reference PCA (sqrt of the eigen values).
Only the |
XV |
|
X_norm |
Vector of sums of squared rows (e.g. |
pca_OADP_proj(): A list with the simple projection X %*% loadings
and the projection based on OADP.
pca_OADP_proj2(): The projection based on OADP only
(a matrix of same size of XV).
X <- readRDS(system.file("testdata", "three-pops.rds", package = "bigutilsr"))
N <- 400; M <- ncol(X)
ind <- sample(nrow(X), N)
# Compute SVD using one part of samples
svd <- svds(X[ind, ], k = 5)
U <- sweep(svd$u, 2, svd$d, '*')
col <- 2:3
plot(U[, col])
points(cbind(0, 0), pch = 8, col = "green", cex = 2)
# Projecting other samples
proj <- pca_OADP_proj(X = X[-ind, ], loadings = svd$v, sval = svd$d)
points(proj$simple_proj[, col], col = "red", pch = 20) # shrunk towards 0
points(proj$OADP_proj[, col], col = "blue", pch = 20) # unshrunkPlease choose more modern alternatives, such as Google Chrome or Mozilla Firefox.