On Tue, 3 Aug 2010 10:00:08 +1000
Glen Barnett wrote:
> This might help some:
>
> RSiteSearch("winsorize")
>
Or
require(sos)
findFn("winsorize")
Liviu
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read t
This might help some:
RSiteSearch("winsorize")
On Sun, Aug 1, 2010 at 11:39 AM, Cecilia Carmo wrote:
> Hi everyone!
>
> #I need a loop or a function that creates a X2 variable that is X1 without
> the extreme values (or X1 winsorized) by industry and year.
>
> #My reproducible example:
> firm<-s
I had to look up winsorized; this should do it:
> #My reproducible example:
> firm<-sort(rep(1:1000,10),decreasing=F)
> year<-rep(1998:2007,1000)
> industry<-rep(c(rep(1,10),rep(2,10),rep(3,10),rep(4,10),rep(5,10),rep(6,10),rep(7,10),rep(8,10),rep(9,10),
+ rep(10,10)),1000)
> X1<-rnorm(1)
> da
Thank you again, but I think I need to do some homework
about the split function, because I'm not understanding it
very well.
Besides, I think I still have a problem. I also need X2 =
X1 winsorized: X2 is equal to X1 between 10%-90%, and is
equal to the 10% value when < 10% and equal to the 90%
This is just following up with the example data you sent. This will
create a list 'result' that will have the subset of data between the
10% & 90%-tiles of the data:
> #My reproducible example:
> firm<-sort(rep(1:1000,10),decreasing=F)
> year<-rep(1998:2007,1000)
> industry<-rep(c(rep(1,10),rep(2
Thank you for your help but I don't understand how can I
have a dataframe with the columns: firm, year, industry,
X1 and X2. Could you help me (again)?
Cecília Carmo
Em Sat, 31 Jul 2010 22:10:38 -0400
jim holtman escreveu:
This will split the data by industry & year and then
return the va
This will split the data by industry & year and then return the values
that include the 80%-tile (>=10% & <= 90%)
# split the data by industry/year
d.s <- split(data, list(data$industry, data$year), drop=TRUE)
result <- lapply(d.s, function(.id){
# get 10/90% values
.limit <- quantile(.id$
Hi everyone!
#I need a loop or a function that creates a X2 variable
that is X1 without the extreme values (or X1 winsorized)
by industry and year.
#My reproducible example:
firm<-sort(rep(1:1000,10),decreasing=F)
year<-rep(1998:2007,1000)
industry<-rep(c(rep(1,10),rep(2,10),rep(3,10),rep(4,1
8 matches
Mail list logo
