Are you saying that
sapply(xx,function(x)weighted.mean(x$H,x$N))
assuming the list of data frames was called xx,
doesn't give the result you want? Could you please
elaborate as to why sapply doesn't give the correct
result?
- Phil Spector
Statistical Computing Facility
Department of Statistics
UC Berkeley
spec...@stat.berkeley.edu
On Wed, 14 Oct 2009, ewaters wrote:
I have browsed the archive, and played around with a whole bunch of ways of
approaching the problem, and I cannot get the answer that I want.
I have a list with 2000 elements. Each element is a data frame with 2
columns. As an example, see element 1999 below.
[[1999]]
H N
6 0.54 26
10 0.31 13
11 0.12 34
13 0.00 38
4 0.59 37
16 0.44 9
19 0.08 13
14 0.64 39
8 0.75 12
24 0.42 26
9 0.61 111
20 0.22 9
Now, I want to caluculate the weighted mean for H in each list element, with
N providing the weights. I can do this fine for an individual list element:
weighted.mean(list[[1999]]$H,list[[1999]]$N)
[1] 0.4456403
or even:
weighted.mean(list[[i]]$H,list[[i]]$N)
[1] 0.5992683
but when I try and apply it in a lopp to give me back the weighted mean for
each list element, I get errors:
list_blah<-matrix(1:2000)
for(i in 1:2000){
+ list_blah[i]=weighted.mean(list[[i]]$H,list[[i]]$N)}
Error in list[[i]] : subscript out of bounds
I am clearly not understanding a basic syntax issue, and I am not overly
skilled at using loops. I have also tried using lapply instead of a for
loop, with the same problem.
Asking for list[i] instead of list[[i]] gives NA results, as would be
expected.
Can anyone shed light?
weighted.mean
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