Team, I tri to use the formula for calculating:
G = QUANTILE('NORMAL', pd). pd has different values, also of 1.
Unfortunately, the log gives me the next error
Does this mean that the function can not provide inverse cumulative distribution function of a real number?
Stepik
Solved taking pd=1 separately
Your argument of QUANTILE() is not right .
since it is a P value, it should be (0,1).
data have;
input pd;
cards;
.1
.2
.3
.4
;
data _null_;
set have;
G = QUANTILE('NORMAL', pd);
put G= pd=;
run;
38 ; 39 40 41 data _null_; 42 set have; 43 G = QUANTILE('NORMAL', pd); 44 put G= pd=; 45 run; G=-1.281551566 pd=0.1 G=-0.841621234 pd=0.2 G=-0.524400513 pd=0.3 G=-0.253347103 pd=0.4 NOTE: 从数据集 WORK.HAVE. 读取了 4 个观测 NOTE: “DATA 语句”所用时间(总处理时间): 实际时间 0.01 秒 CPU 时间 0.00 秒
Solved taking pd=1 separately
Sorry. I have to leave now. I will take a look tomorrow.
But maybe @Rick_SAS could give you a hand. He is good at this.
Hello @Stepik,
I think you just need to handle the cases pd=0 and pd=1 separately in the calculation of G and N:
if pd in (0 1) then N=pd; else do; G = QUANTILE('NORMAL', pd); N = CDF('NORMAL', G/SQRT(1-R)+SQRT(R/(1-R))*QUANTILE('NORMAL',0.999)); end;
Alternatively, since N=pd implies RWA1=0, you can also put the entire block of your assignment statements into the ELSE branch:
if pd in (0 1) then RWA1=0; else do; ... your code ... end;
(before the RETURN statement).
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