If there are many variables, I'd then suggest the data.table package:
library(data.table)
dt=data.table(x)
dt[,lapply(.SD, function(x)weighted.mean(x,myweight)), keyby=c('group',
'myweek')]
The '.SD' is an abbreviation for all the variables in the data table
(excluding the grouping variables). There's an .SDcols= 'variables of
interest' option if you want to limit the dozens of variables to only some
of them. Or, in the data.table(x) statement, you could limit the created
data table to only the variables your interested in.
As an added benefit, the data.table approach is amazingly fast (particularly
when there are numerous grouping categories)
--
View this message in context:
http://r.789695.n4.nabble.com/weighted-mean-by-week-tp4636814p4636825.html
Sent from the R help mailing list archive at Nabble.com.
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
