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Figure 3.28
Clouds of points for the unscaled and scaled covariance matrices in (3.30).
Usage
PCAbipl (X = Ocotea.data[,3:8], G = NULL, X.new.samples = NULL,
X.new.vars = NULL, scaled.mat = FALSE, e.vects = 1:ncol(X),
dim.biplot = c(2,1,3), adequacies.print = FALSE,
alpha = 0.95, alpha.3d = 0.1, aspect.3d = "iso",
ax.col.3d = "black", ax = 1:sum(c(ncol(X),ncol(X.new.vars))),
ax.name.col = rep("black",sum(c(ncol(X),ncol(X.new.vars)))),
ax.name.size = 0.75, ax.type = c("predictive","interpolative"),
ax.col = list(ax.col = rep("grey",sum(c(ncol(X),
ncol(X.new.vars)))), tickmarker.col = rep("grey",
sum(c(ncol(X),ncol(X.new.vars)))), marker.col = rep("black",
sum(c(ncol(X),ncol(X.new.vars))))),
between = c(1,-1,0,1), between.columns = -1,
cex.3d = 0.6, char.legend.size = c(1.2, 0.7), c.hull.n = 10,
colour.scheme = NULL, colours = c(1:8,3:1),
colours.means = NULL, col.plane.3d = "lightgrey",
col.text.3d = "black", columns = 1, constant = 0.1,
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