Well, I have seasonal data and I want to mimic weekly data through moving bootstrapping. But I can't find the most suitable sample and I just piece them together. Is the concept that the mean and var come from AR right? And how to use it in the bootstrapping?
And I want to get the distribution of them.
proc import datafile='C:\Users\user\Desktop\\morgan.csv'
out= morgan dbms=dlm; delimiter=',';
format Date yymm.;
getnames=yes;
run;
data morgan;
set a;
PXlag = lag1(PX );
run;
proc autoreg data=b;
model PX = PXlag / lagdep=PXlag;
output out=resid mean standards;
r=resid;
run;
proc surveyselect data=b out=outboot
seed=30459584
method=urs
samprate=1
outhits
rep=1000;
run;
proc univariate data=outboot;
var x;
by Replicate;
output out=outall kurtosis=curt;
run;
proc univariate data=outall;
var curt;
output out=final pctlpts=2.5, 97.5 pctlpre=ci;
run;
If this question was about data simulation, post it at IML forum.
If it was about Time Series Analysis,post it at Forecast forum.
H i @Ksharp,
Please do not suggest that people post questions to the SAS/IML forum unless the question is related to IML. If you want to get my attention, just use my @Rick_SAS name in your response. I will get notified that someone mentioned me in a discussion and I will look at it if I have time. Thanks!
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