ssMRCD (version 1.1.0)

scores: Calculate Scores for local sparse PCA

Description

Calculate Scores for local sparse PCA

Usage

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

Value

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

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.

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)