ssMRCD (version 1.1.0)

plot_score_distances: Distance-distance plot of scores of PCA

Description

Distance-distance plot of scores of PCA

Usage

plot_score_distances(X, PC, groups, ssMRCD, k, ...)

Value

Returns distance-distance plot of orthogonal and score distance.

Arguments

X

data matrix.

PC

loadings from PCA.

groups

vector containing group assignments.

ssMRCD

ssMRCD object.

k

integer of how many components should be used.

...

other input arguments, see details.

Details

Additional parameters that can be given to the function are:

shape	point shape
size	point size
alpha	transparency

Examples

# set seed
set.seed(236)

data = matrix(rnorm(2000), ncol = 4)
groups = sample(1:10, 500, replace = TRUE)
W = time_weights(N = 10, c(3,2,1))

# calculate covariance matrices
covs = ssMRCD(data, groups = groups, weights = W, lambda = 0.3)

# sparse PCA
pca = sparsePCAloc(eta = 0.3, gamma = 0.7, cor = FALSE, COVS = covs$MRCDcov,
             n_max = 1000, increase_rho = list(TRUE, 50, 1), trace = FALSE)

# plot score distances
plot_score_distances(PC = pca$PC,
                     groups = groups,
                     X = data,
                     ssMRCD = covs,
                     k = 2,
                     alpha = 0.4,
                     shape = 16,
                     size = 2)