[R] weighted.mean and tapply (again)
james.holtman@convergys.com
james.holtman at convergys.com
Wed May 25 17:56:37 CEST 2005
> x.1 <- read.table('clipboard',header=T)
> x.1
GROUP VALUE FREQUENCY
1 2 2 78
2 2 3 40
3 2 4 16
4 2 5 3
5 2 6 1
6 2 8 1
7 3 3 19
8 3 4 10
9 3 5 19
10 3 6 4
> by(x.1, x.1$GROUP, function(x) weighted.mean(x$VALUE, x$FREQUENCY))
x.1$GROUP: 2
[1] 2.654676
---------------------------------------------------------------------------
x.1$GROUP: 3
[1] 4.153846
>
Jim
__________________________________________________________
James Holtman "What is the problem you are trying to solve?"
Executive Technical Consultant -- Office of Technology, Convergys
james.holtman at convergys.com
+1 (513) 723-2929
Dan Bolser
<dmb at mrc-dunn.cam.ac. To: R mailing list <r-help at stat.math.ethz.ch>
uk> cc:
Sent by: Subject: [R] weighted.mean and tapply (again)
r-help-bounces at stat.m
ath.ethz.ch
05/25/2005 11:33
I read answers to questions including the words "tapply" and
"weighted.mean", but I didn't understand either the problem (data) or the
solution provided.
Here is my question ...
> dat[1:10,]
GROUP VALUE FREQUENCY
1 2 2 78
2 2 3 40
3 2 4 16
4 2 5 3
5 2 6 1
6 2 8 1
7 3 3 19
8 3 4 10
9 3 5 19
1 3 6 4
For each GROUP, I would like to calculate the weighted.mean of VALUE using
the FREQUENCY as the weight, so for the snippet of data shown that would
be...
group.2 <- weighted.mean(c(2,3,4,5,6,8),c(78,40,16,3,1,1))
group.3 <- weighted.mean(c(3,4,5,6), c(19,10,19,4))
> cbind(rbind(2,3),rbind(group.2,group.3))
[,1] [,2]
group.2 2 2.654676
group.3 3 4.153846
I would like to use tapply to automatically do this across the whole
dataset (dat) - which includes lots of other distinct grouping factors,
however, like I said, I couldn't understand (and therefore apply to my
data) any of the other solutions I found, so any help here would be
greatly appreciated!
All the best,
Dan.
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