scores: Calculate Scores for local sparse PCA

In ssMRCD: Spatially Smoothed MRCD Estimator

Calculate Scores for local sparse PCA

Description

Calculate Scores for local sparse PCA

Usage

scores(X, PC, groups, ssMRCD = NULL)

Arguments

X	data set as matrix.
PC	loading matrix.
groups	vector of grouping structure (numeric).
ssMRCD	ssMRCD object used for scaling X. If NULL no scaling and centering is performed.

Value

Returns a list with scores and univariately and locally centered and scaled observations.

See Also

ssMRCD, scale_ssMRCD

Examples

# create data set
x1 = matrix(runif(200), ncol = 2)
x2 = matrix(rnorm(200), ncol = 2)
x = list(x1, x2)

# create weighting matrix
W = matrix(c(0, 1, 1, 0), ncol = 2)

# calculate ssMRCD
loccovs = ssMRCD(x, weights = W, lambda = 0.5)

# calculate PCA
pca = sparsePCAloc(eta = 1, gamma = 0.5, cor = FALSE,
                   COVS = loccovs$MRCDcov,
                   increase_rho = list(FALSE, 20, 1))

# calculate scores
scores(X = rbind(x1, x2), PC = pca$PC,
       groups = rep(c(1,2), each = 100), ssMRCD = loccovs)

ssMRCD documentation built on Sept. 11, 2024, 5:14 p.m.