the function that generates the simulation data set
dataSim(n = 200, p = 20, bLength = 4, a = c(0.9, 0.5, 0),
SD = c(10, 5, 2), eps = 0, eta = 25, setting = "3", seed = 123,
vc = NULL)number of observations
number of variables
the number of correlated variables in the first k blocks
numveric vector of length k+1 that contains the correlations between the variables in each block (the last block contains uncorrelated variables); by default is (0.9, 0.5, 0)
numveric vector of length k+1 that contains the standard deviation of the variables in each block (the last block contains uncorrelated variables); by default is (10, 5, 2)
proportion of outliers, default is 0
parameter that contols the outlyingness, default is 25
type of outliers: setting="1" generates the outliers which are outlying in the first two variables in the second block; setting="2" generates
score outliers; setting="3" generates the orthogonal outliers which are easy to detect (the setting used in Hubert, et al (2016)); default is "3"
random seed used to simulate the data
controls the direction of the score outliers within the PC subspace, default is NULL
a list with components
generated data matrix
row indices of outliers
Correlation matrix of the data
Covariance matrix of the data