Thank you everyone. After thinking about each response, I realized a fairly
simple solution is available (obviously, other suggested approaches work as
well):
stopifnot(length(x) == length(y); stopifnot(length(x) > 0)
r <- list()
for (i in 1:length(x) ) {
r[[i]] <- cor(x = dat[, x[i] ], y = dat[, y[i] ])
}
print(r)
On Mon, Sep 10, 2018 at 11:30 AM Berry, Charles <ccbe...@ucsd.edu> wrote:
> I have a sense of deja vu:
>
> https://www.mail-archive.com/r-help@r-project.org/msg250494.html
>
> There is some good advice there.
>
> > On Sep 9, 2018, at 3:49 PM, David Disabato <ddisa...@gmail.com> wrote:
> >
> > Hi R-help,
> >
> > I am trying to create a for loop with multiple iteration indexes. I don't
> > want to use two different for loops nested together because I don't need
> > the full matrix of the two indexes, just the diagonal elements (e.g.,
> i[1]
> > & j[1] and i[2] & j[2], but not i[1] & j[2]). Is there a way to specify
> > both i and j in a single for loop? Here is a simplified example of
> > pseudo-code where x and y are equally sized character vectors with column
> > names and dat is their dataframe (obviously this code doesn't run in R,
> but
> > hopefully you perceive my goal):
> >
> > r <- list()
> > n <- 0
> > for (i in x; j in y) {
> > n <- n + 1
> > r[[n]] <- cor(x = dat[, i], y = dat[, j])
> > }
> > print(r)
> >
> > I realize there are other solutions to this particular correlation
> example,
> > but my actual problem is much more complicated, so I am hoping for a
> > solution that generalizes across any code within the for loop.
>
> A more aRtful way (than a for loop) to approach this is with mapply:
>
>
> i <- head(colnames(mtcars))
> j <- tail(colnames(mtcars))
>
> r <- mapply(function(i, j, dat) cor( x = dat[, i], y = dat[, j]),
> i=i , j=j , MoreArgs = list( dat = mtcars),
> SIMPLIFY = FALSE, USE.NAMES = FALSE)
>
>
> and if you want, maybe USE.NAMES = paste(i, j, sep="_")
>
> Chuck
>
>
--
David J. Disabato, M.A.
Clinical Psychology Doctoral Student
George Mason University
ddisa...@gmu.edu
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