Plots of score distribution
plot_scores(X, PC, groups, ssMRCD, ...)Returns histograms of scores for component k.
data matrix.
loadings from PCA.
vector containing group assignments.
ssMRCD object.
other input arguments, see details.
Additional parameters that can be given to the function are:
shape | point shape |
size | point size |
alpha | transparency |
k | integer, which component scores should be plotted |
# 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$MRCDcov,
n_max = 1000, increase_rho = list(TRUE, 50, 1), trace = FALSE)
# plot score distances
plot_scores(PC = pca$PC,
groups = groups,
X = data,
ssMRCD = covs,
k = 1,
alpha = 0.4,
shape = 16,
size = 2)
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