On Feb 22, 2010, at 8:27 PM, ewaters wrote:
Related questions to this have been asked before, but I have tried all
options they gave me unsuccessfully (do.call and unlist).
I start with three lists of summary statistics, 100 elements each,
which I
bind together:
None of this represents data that are too large to include in an
unambiguous fashion with dump or dput. Why do youy persist in asking
questions whare there remain ambiguities?
statslist <- as.data.frame(cbind (means, vars, mcrs))
I then take 100 samples of this data frame of varying lengths:
stats <- lapply (1:100, function (dummy) {
statslist[sample(nrow(statslist), (sample (10:20, 1, replace = TRUE)),
replace = TRUE),]})
So what are readers supposed to do? Create similar structures and work
on them?
It returns basically what I want:
stats[[i]]
means vars mcrs
71 1.81 3.832222 2.92725
9 2.56 8.127677 4.734874
91 3.44 9.66303 5.24902
68 0.14 0.1216162 0.008686869
except that:
is.list(stats[[i]]$means)
[1] TRUE
So lapply on a list returns a list? Where is the surprise?
I don't want this to be a list, because I want to do regressions
using the
variable which are in columns, which apparently R won't do if they
are in
lists.
I have tried every possible combination of working with do.call,
rbind,
as.data.frame, etc to get this into matrix form to no avail.
I have also tried using sapply instead of lapply, but that returns
vectors
which again, R doesn't want to do regression on.
???? R does not want to do regressions on vectors??? How can that be?
Any tips would be very much appreciated, been going around in
circles for a
while here.
Reproducible data would answer these questions and prevent this
"circular" process that _you_ are responsible for allowing to continue.
--
David.
Edward Waters
PhD Student UNSW
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