plot_scores: Plots of score distribution

In ssMRCD: Spatially Smoothed MRCD Estimator

Plots of score distribution

Description

Plots of score distribution

Usage

plot_scores(X, PC, groups, ssMRCD, ...)

Arguments

X	data matrix.
PC	loadings from PCA.
groups	vector containing group assignments.
ssMRCD	ssMRCD object.
...	other input arguments, see details.

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

Value

Returns histograms of scores for component k.

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_scores(PC = pca$PC,
            groups = groups,
            X = data,
            ssMRCD = covs,
            k = 1,
            alpha = 0.4,
            shape = 16,
            size = 2)

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