How can confidence intervals be numerically visualized in corrplot()?

Question

In corrplot(), is it possible to visualize confidence intervals numerically below the coefficients?

library(corrplot)
M <- cor(mtcars)


cor.mtest <- function(mat, conf.level = 0.95){
  mat <- as.matrix(mat)
  n <- ncol(mat)
  p.mat <- lowCI.mat <- uppCI.mat <- matrix(NA, n, n)
  diag(p.mat) <- 0
  diag(lowCI.mat) <- diag(uppCI.mat) <- 1
  for(i in 1:(n-1)){
    for(j in (i+1):n){
      tmp <- cor.test(mat[,i], mat[,j], conf.level = conf.level)
      p.mat[i,j] <- p.mat[j,i] <- tmp$p.value
      lowCI.mat[i,j] <- lowCI.mat[j,i] <- tmp$conf.int[1]
      uppCI.mat[i,j] <- uppCI.mat[j,i] <- tmp$conf.int[2]
    }
  }
  return(list(p.mat, lowCI.mat, uppCI.mat))
}

res1 <- cor.mtest(mtcars,0.95)
res2 <- cor.mtest(mtcars,0.99)

I would like to add to the following plot, low=res1[[2]] and upp=res1[[3]] confidence intervals as numbers below the correlation coefficients.

corrplot(M, method="number")

Answer 1

corrplot is a pretty text text() table. So we can try adding additional text on it.

Continuing from your example:

corrplot(cor(mtcars), method="number")

We form the confidence interval labels:

conf <- paste0("[", format(res1[[2]], digits=1), ":", format(res1[[3]], digits=1), "]")

And add them as text to the existing corrplot:

xs <- row(res1[[1]])
ys <- (ncol(res1[[1]])+1) - col(res1[[1]])
text(xs, ys, conf, pos=1, cex=0.5)

NOTE: seems like y=1 starts on the top so we need to invert it (that's why ys expression is more complicated than xs.

Here is the result: