Have a look at function ave(), e.g.,
set.seed(1)
(df <- data.frame(Group=rep(c("Group1","Group2","Group3"), each=10),
Value=c(rexp(10, 1), rexp(10, 4), rexp(10, 10)))[sample(1:30,30),])
edf <- function(x) ecdf(x)(x)
df$edf <- with(df, ave(Value, Group, FUN = edf))
df
I hope it helps.
Best,
Dimitris
On 8/17/2011 12:42 PM, Marius Hofert wrote:
Dear all,
First, let's create some data to play around:
set.seed(1)
(df<- data.frame(Group=rep(c("Group1","Group2","Group3"), each=10),
Value=c(rexp(10, 1), rexp(10, 4), rexp(10,
10)))[sample(1:30,30),])
## Now we need the empirical distribution function:
edf<- function(x) ecdf(x)(x) # empirical distribution function evaluated at x
## The big question is how one can apply the empirical distribution function to
## each subset of df determined by "Group", so how to apply it to Group1, then
## to Group2, and finally to Group3. You might suggest (?) to use tapply:
(edf.<- tapply(df$Value, df$Group, FUN=edf))
## That's correct. But typically, one would like to obtain not only the values,
## but a data.frame containing the original information and the new
(edf-)values.
## What's a simple way to get this? (one would be required to first sort df
## according to Group, then paste the values computed by edf to the sorted df;
## seems a bit tedious).
## A solution I have is the following (but I would like to know if there is a
## simpler one):
(edf..<- do.call("rbind", lapply(unique(df$Group), function(strg){
subdata<- subset(df, Group==strg) # sub-data
subdata<- cbind(subdata, edf=edf(subdata$Value))
})) )
Cheers,
Marius
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--
Dimitris Rizopoulos
Assistant Professor
Department of Biostatistics
Erasmus University Medical Center
Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands
Tel: +31/(0)10/7043478
Fax: +31/(0)10/7043014
Web: http://www.erasmusmc.nl/biostatistiek/
______________________________________________
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and provide commented, minimal, self-contained, reproducible code.
