PlotCorr(x, cols = colorRampPalette(c(Pal()[2], "white",
                                      Pal()[1]), space = "rgb")(20),
         breaks = seq(-1, 1, length = length(cols) + 1),
         border = "grey", lwd = 1,
         args.colorlegend = NULL, xaxt = par("xaxt"), yaxt = par("yaxt"),
         cex.axis = 0.8, las = 2, mar = c(3, 8, 8, 8), mincor = 0,
         main = "", clust = FALSE, ...)

m <- cor(d.pizza[,sapply(d.pizza, IsNumeric, na.rm=TRUE)], use="pairwise.complete.obs")

PlotCorr(m, cols=colorRampPalette(c("red", "black", "green"), space = "rgb")(20))
PlotCorr(m, cols=colorRampPalette(c("red", "black", "green"), space = "rgb")(20),
         args.colorlegend=NA)

m <- PairApply(d.diamonds[, sapply(d.diamonds, is.factor)], CramerV, symmetric=TRUE)
PlotCorr(m, cols = colorRampPalette(c("white", "steelblue"), space = "rgb")(20),
         breaks=seq(0, 1, length=21), border="black",
         args.colorlegend = list(labels=sprintf("%.1f", seq(0, 1, length = 11)), frame=TRUE)
)
title(main="Cramer's V", line=2)
text(x=rep(1:ncol(m),ncol(m)), y=rep(1:ncol(m),each=ncol(m)),
     label=sprintf("%0.2f", m[,ncol(m):1]), cex=0.8, xpd=TRUE)

# Spearman correlation on ordinal factors
csp <- cor(data.frame(lapply(d.diamonds[,c("carat", "clarity", "cut", "polish",
                      "symmetry", "price")], as.numeric)), method="spearman")
PlotCorr(csp)

m <- cor(mtcars)
PlotCorr(m, col=Pal("RedWhiteBlue1", 100), border="grey",
         args.colorlegend=list(labels=Format(seq(-1,1,.25), digits=2), frame="grey"))

# display only correlation with a value > 0.7
PlotCorr(m, mincor = 0.7)
x <- matrix(rep(1:ncol(m),each=ncol(m)), ncol=ncol(m))
y <- matrix(rep(ncol(m):1,ncol(m)), ncol=ncol(m))
txt <- Format(m, digits=3, ldigits=0)
idx <- upper.tri(matrix(x, ncol=ncol(m)), diag=FALSE)

# place the text on the upper triagonal matrix
text(x=x[idx], y=y[idx], label=txt[idx], cex=0.8, xpd=TRUE)

# or let's get rid of all non significant correlations
p <- PairApply(mtcars,  function(x, y) cor.test(x, y)$p.value, symmetric=TRUE)
# or somewhat more complex with outer
p0 <- outer(1:ncol(m),  1:ncol(m),
           function(a, b)
             mapply(
               function(x, y) cor.test(mtcars[, x], mtcars[, y])$p.value,
               a, b))
# ok, got all the p-values, now replace > 0.05 with NAs
m[p > 0.05] <- NA
PlotCorr(m)

# the text
n <- ncol(m)
text(x=rep(seq(n), times=n),
     y=rep(rev(seq(n)), rep.int(n, n)),
     labels=Format(m, digits=2, na.form=""),
     cex=0.8, xpd=TRUE)
# the text could also be set with outer, but this function returns an error,
# based on the fact that text() does not return some kind of result
# outer(X = 1:nrow(m),  Y = ncol(m):1,
#  FUN = "text", labels = Format(m, digits=2, na.form = ""),
#  cex=0.8, xpd=TRUE)


# put similiar correlations together
PlotCorr(m, clust=TRUE)

# same as
idx <- order.dendrogram(as.dendrogram(
          hclust(dist(m), method = "mcquitty")
       ))
PlotCorr(m[idx, idx])