# NOT RUN {
# Generate the vector of PCA.ContCont values when rho_T0S=.3, rho_T1S=.9,
# sigma_T0T0=2, sigma_T1T1=2,sigma_SS=2, and
# the grid of values {-1, -.99, ..., 1} is considered for the correlations
# between T0 and T1:
PCA <- PCA.ContCont(T0S=.3, T1S=.9, T0T0=2, T1T1=2, SS=2,
T0T1=seq(-1, 1, by=.01))
# Plot the results:
plot(PCA)
# Same plot but add the percentages of PCA values that are equal to or larger
# than the midpoint values of the bins
plot(PCA, Labels=TRUE)
# Plot of the cumulative distribution of PCA
plot(PCA, Typ="CumPerc")
# }
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