Bill,
For package-specific questions, you should email the package maintainer
(for corrgram, that's me).
Michael Friendly's paper on corrgrams includes an example of partial
correlations. The code to reproduce his example is hiding in the "tests"
directory of the corrgram sourcecode zip file. Here it is below.
Kevin
# Figure 8
require(Matrix) # For block diagonal function
partial <- function(r, xvar){
# r is a correlation matrix
# Calculate partial correlation of y|x
yvar <- setdiff(colnames(r), xvar)
ri <- r[yvar,yvar] - r[yvar,xvar] %*% solve(r[xvar,xvar]) %*% r[xvar,yvar]
s <- diag(ri)
s <- diag(sqrt(1/s))
ri <- s %*% ri %*% s
ri <- as.matrix(bdiag(ri, r[xvar, xvar]))
diag(ri) <- 1 # Should already be 1, but could be 1 + epsilon
colnames(ri) <- rownames(ri) <- c(yvar, xvar)
return(ri)
}
vars8a <- c("Gratio", "Rep78", "Rep77", "Hroom", "Trunk", "Rseat",
"Length", "Weight", "Displa", "Turn")
vars8b <- c("MPG", "Price")
vars8 <- c(vars8a, vars8b)
auto.cor <- cor(auto[, vars8], use="pair")
auto.par <- partial(auto.cor, vars8b)
corrgram(auto.par, lower.panel=panel.pie, upper.panel=panel.pie,
main="Auto data, partialing out Price,MPG")
On Tue, May 13, 2014 at 4:33 PM, Bill Anderegg <ander...@princeton.edu>wrote:
> Hi, I am trying to construct a correlelogram plot but plot partial
> correlation
> coefficients, rather than normal coefficients. I've been using the
> corrgram() and ggm() libraries to do correlelograms and partial correlation
> analysis respectively, but I can't figure out how to combine them. Here is
> my code (my dataset is "climvar4" and is a matrix with 11 climate
> variables with 51
> observations per variable. so in each cell of the correlelogram I want to
> display the partial correlation between variable x and variable y, while
> accounting for all
> other variables):
>
> library(ggm)
> library(corrgram)
> panel.shadeNtextP <- function (x, y, corr = NULL, col.regions, ...)
> {
> corr <- pcor(x, y, var(climvar4))
> results <- pcor.test(corr,10,51)
> est <- results$p.value
> stars <- ifelse(est < 5e-4, "***",
> ifelse(est < 5e-3, "**",
> ifelse(est < 5e-2, "*", "")))
> ncol <- 14
> pal <- col.regions(ncol)
> col.ind <- as.numeric(cut(corr, breaks = seq(from = -1, to = 1,
> length = ncol + 1),
> include.lowest = TRUE))
> usr <- par("usr")
> rect(usr[1], usr[3], usr[2], usr[4], col = pal[col.ind],
> border = NA)
> box(col = "lightgray")
> on.exit(par(usr))
> par(usr = c(0, 1, 0, 1))
> r <- formatC(corr, digits = 2, format = "f")
> cex.cor <- .8/strwidth("-X.xx")
> fonts <- ifelse(stars != "", 2,1)
> # option 1: stars:
> text(0.5, 0.4, paste0(r,"\n", stars), cex = cex.cor)
> # option 2: bolding:
> #text(0.5, 0.5, r, cex = cex.cor, font=fonts)
> }
> corrgram(climvar4, type="data", order=F, lower.panel=panel.shadeNtextP,
> upper.panel=NULL, cex=1.3)
>
> Thanks so much in advance!
>
> Bill
>
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> posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
--
Kevin Wright
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