On Feb 27, 2012 at 9:30pm Joyous Fisher wrote:
> Q: is there a way to do princomp or another method where every row has at
> least one missing column?
You have several options. Try function nipals in packages ade4 and plspm.
Also look at package pcaMethods (on Bioconductor), where you will find
Hello again,
> Q: is there a way to do princomp or another method where every row has at
> least one missing column?
See also package 'psych', function 'principal'. You can impute mean or
median to NAs.
Rui Barradas
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Hello,
> I could find the maximal set of columns such that there exists a subset of
> rows with non NA values for every column in the set - what is an
> efficient
> way to do that?
Try 'na.exclude' on the transpose matrix.
Example:
set.seed(1)
x <- matrix(1:200, ncol=25)
f <- function(x){x[sam
Hello,
I have a matrix with 267 columns, all rows of which have at least one
column missing (NA).
All three methods i've tried (pcs, princomp, and prcomp) fail with either
"Error in svd(zsmall) : infinite or missing values in 'x'" (latter two)
or
"Error in cov.wt(z) : 'x' must contain finite va
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