Using R, generate data and store it in the R variable x using the commands set.seed(3)
x=rmul(100,p=5,mar.fun=ghdist,h=.2,rho=.0)
x[,1]=rlnorm(100)^2 This creates five independent random variables, the last four of which have symmetric, heavy-tailed distributions, and the first has a skewed distribution with 18 outliers. The population value of Pearson’s correlation, among all pairs of variables, is zero. Use regpca to perform the classic PCA and verify that for two and three components, the cumulative proportion of variance is 0.856 and 0.920, respectively, suggesting that two or three components are needed to capture the variability in the data.