statistics - How to return significant matches in R corrplot? -


i return significant matches following result figure fig. 1

library("corrplot")  m <- cor(mtcars)  # http://www.sthda.com/english/wiki/visualize-correlation-matrix-using-correlogram cor.mtest <- function(mat, ...) {     mat <- as.matrix(mat)     n <- ncol(mat)     p.mat<- matrix(na, n, n)     diag(p.mat) <- 0     (i in 1:(n - 1)) {         (j in (i + 1):n) {             tmp <- cor.test(mat[, i], mat[, j], ...)             p.mat[i, j] <- p.mat[j, i] <- tmp$p.value         }     }   colnames(p.mat) <- rownames(p.mat) <- colnames(mat)    p.mat }  n <- length(mtcars) -1 p.mat <- cor.mtest(mtcars) head(p.mat[, 1:n]) ids <- seq(1,n)   corrplot(m, type="upper", order="hclust", tl.pos=c("td"), method="circle",       tl.cex = 0.5, tl.col = 'black',      diag = false, p.mat = p.mat,      sig.level = 0.0000005)

fig. 1 output

enter image description here

expected output

cyl: wt hp disp: wt hp cyl ...

r: 3.3.1
os: debian 8.5

the usual warnings regarding multiple testing apply here.

i write vectorized cor.test (there reason not available stats package, see above).

cor.test.all <- function(df) {   #based on code stats:::cor.test.default   #see license() license    #two-sided test pearson correlation    #without adjustment of p-values   #no na treatment   r <- cor(df)   df <- nrow(df) - 2l   t <-  sqrt(df) * r/sqrt(1 - r^2)   2 * pmin(pt(t, df), pt(t,  df, lower.tail = false)) }  cor.p <- cor.test.all(mtcars) diag(cor.p) <- na res <- which(cor.p < 0.0000005, arr.ind = true)  split(colnames(cor.p)[res[,2]], rownames(cor.p)[res[,1]]) #$am #[1] "gear" # #$cyl #[1] "mpg"  "disp" "hp"   "wt"   "vs"   # #$disp #[1] "mpg" "cyl" "hp"  "wt"  # #$gear #[1] "am" # #$hp #[1] "mpg"  "cyl"  "disp" # #$mpg #[1] "cyl"  "disp" "hp"   "wt"   # #$vs #[1] "cyl" # #$wt #[1] "mpg"  "cyl"  "disp"

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