Hi Everyone,
I want to do a process similar to finding moving percentile.
However, for each record, I want to look back 500 records (excluding the current record) and extract the value of the 475th largest record (it is not the same as 95 percentile in SAS).
I prefer this way to percentile since it is comparable with other software I use and I can control the value better.
So for the data below, for the first record, the value-475 should be 476.
Thank you for your help.
HHC
data have;
do value=1 to 1000;output; end;
;run;
You mean look forward ?
data have; do value=1 to 1000; output; end; ; run; data want; set have nobs=nobs; array x{99999} _temporary_; do i=_n_+1 to min(nobs,_n_+499); set have(rename=(value=v)) point=i; x{i}=v; end; _25th=largest(25,of x{*}); call missing(of x{*}); drop i v; run;
Xia Keshan
I think you mean 25th largest?
data have;
do value=1 to 1000;
output;
end;
;
run;
data want;
array t(0:499) _temporary_;
set have;
t(mod(_n_,500))=value;
if _n_>499 then
_25th=largest(25,of t(*));
run;
Haikuo
Hi,
It is almost what I want.
However, the first record value for _25th should be 476.
file want should look like:
value _25th
1 476
2 477
...
HHC
This?
data want;
array t(0:499) _temporary_;
set have;
t(mod(_n_,500))=value;
if _n_>499 then do;
_25th=largest(25,of t(*));
n+1;
output;
end;
drop value;
rename n=value;
run;
Yes it is the what I want. But I want to keep the original 1000 records. Right now the last 499 records are gone.
If I have to do DO LOOP through this code, each time, the data is reduced by 499.
HHC
You mean look forward ?
data have; do value=1 to 1000; output; end; ; run; data want; set have nobs=nobs; array x{99999} _temporary_; do i=_n_+1 to min(nobs,_n_+499); set have(rename=(value=v)) point=i; x{i}=v; end; _25th=largest(25,of x{*}); call missing(of x{*}); drop i v; run;
Xia Keshan
Available on demand!
Missed SAS Innovate Las Vegas? Watch all the action for free! View the keynotes, general sessions and 22 breakouts on demand.
Learn how use the CAT functions in SAS to join values from multiple variables into a single value.
Find more tutorials on the SAS Users YouTube channel.