pr[in]comp: predict single observation when data has colnames (PR#8324)

To my knowledge, this has not been reported previously, and doesn't
seem to have been changed in R-devel or R-patched.

If M is a matrix with coloumn names, and

mod <- prcomp(M)  # or princomp

then predicting a single observation (row) with predict() gives the
error

Error in scale.default(newdata, object$center, object$scale) : 
	length of 'center' must equal the number of columns of 'x'

This doesn't happen if M doesn't have coloumn names.

For instance:

M <- matrix(rnorm(30), ncol = 3)
mod <- prcomp(M[-1,])
predict(mod, newdata = M[1,, drop = FALSE])

           PC1       PC2       PC3
[1,] -1.666191 -2.333012 -1.424587

colnames(M) <- 1:3
mod <- prcomp(M[-1,])
predict(mod, newdata = M[1,, drop = FALSE])

Error in scale.default(newdata, object$center, object$scale) : 
	length of 'center' must equal the number of columns of 'x'


I believe the problem is the line

        newdata <- newdata[, nm]

in predict.prcomp (line 106 of prcomp.R) and predict.princomp (line 11
of princomp-add.R), which should probably be

        newdata <- newdata[, nm, drop = FALSE]