I am re-posting this question in hope of getting any answer.
I am fitting different distributions to a data set. I am using the following code:
proc capability data=pdlsf; specs usl=usl; var result; histogram / normal(indices) Lognormal(indices); by par1 par2; inset mean std cv n ppk="Ppk" normal(ESTPCTGTR) normal(ksdpval)/ cfill=white pos=ne; run; quit;
When running the code as expected I get a nice quantile table with predefined quantiles like
1%, 5%, 10%,...., 99%.
What I need is to get some certain quantiles that is not predefined. Let's say for some calculation I need to get 99.22% quantile estimated by lognormal.
Can I get that non-pre-defined quantile with proc capability? if yeas, how? If not, what proc step can do that for me?
A desired outcome could be something like the following table which is basically a quantile table generated by proc capability step with only difference that I defined 99.22% to be calculated in this table.
Quantiles for lognormal Distribution quantile observed estimated 1 12 11.422 99.22 21 19.485
I'm not familiar with Proc Capability, so this may be of no help at all, but here is a paper that discusses the best SAS procedures for generating custom percentiles: https://www.lexjansen.com/wuss/2014/114_Final_Paper_PDF.pdf
It might be that you would need to define/determine the distribution using Proc Capability and then the percentiles with another procedure. A bit of a pain to use multiple procedures, I know, but since no one else has responded, I thought I'd at least suggest supplemental procedures.
Jim
Here is how to get the observed quantile which does not depend on the assumed distribution:
proc capability data=sashelp.heart;
var cholesterol;
output out=perc n=n median=med geomean=geom pctlpts=99.22 pctlpre=pChol PCTLNDEC=2;
run;
proc print data=perc label noobs; run;
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