You could try something like this.
library(plyr)
ddply(pool, .(ym), function(z){
weighted.mean(x= z$SMM, w = z$wght)
})
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
+ 32 2 525 02 51
+ 32 54 43 61 85
thierry.onkel...@inbo.be
www.inbo.be
To call in the statistician after the experiment is done may be no more than
asking him to perform a post-mortem examination: he may be able to say what the
experiment died of.
~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data.
~ Roger Brinner
The combination of some data and an aching desire for an answer does not ensure
that a reasonable answer can be extracted from a given body of data.
~ John Tukey
-----Oorspronkelijk bericht-----
Van: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] Namens
Bond, Stephen
Verzonden: dinsdag 7 februari 2012 15:55
Aan: r-help@r-project.org
Onderwerp: [R] Weighted mad
Greetings UseRs,
Pls advise if there is a way to write a func that can be supplied to aggregate
to compute weighted MeanAbsolute Dev (MAD). I am having trouble passing the
correct weights from each group level and cannot see the code behind aggregate.
But maybe 'aggregate' is not the best way to do that.
> m1 <-
> aggregate(pool[,c("SMM")],by=list(time=pool$ym),weighted.mean,w=pool$wght)
Error in weighted.mean.default(X[[1L]], ...) :
'x' and 'w' must have the same length
Apparently the grouping does not work on the additional argument. I am using
weighted mean here just to be explicit and avoid supplying a custom function
gor weighted MAD, which is not difficult to write by itself. It's making it
work with aggreagte that is the problem.
> aggregate
function (x, ...)
UseMethod("aggregate")
<environment: namespace:stats>
Does not show anything...
Stephen B
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