Hello All,   I am starting to do more simulations and have a general question regarding simulating a lognormal distribution.  I have existing data that looks like the following (I've fitted a lognormal curve to the data). I would like to simulate more data using the MLE estimated shape, scale and location parameters for the exisiting data.  I noticed the RAND function does not support location, shape or scale for the lognormal distribution. How can I incorporate these parameters so that I can simulate data to look like my original data? I thought I could do Y = location parameter + scale parameter*X, where X =RAND("LOGNORMAL"). Am I on the right track here? Any help appreciated!!!   ... View more

Hello,   I am trying to simulate data from a gamma distribution. I originally used the RAND function, from my understanding this is a newer function. However, I also tried the older function RANGAM. When using the same shape (and scale) parameters I get very different graphs when plotting the data.  I'm obviously not understanding something correctly, could anyone advise on why one would use RAND vs. RANDGAM? I assumed there really shouldn't be any major differences.   Sample Code I tried %let shape =0.15; %let scale = 0.25;   data test; do i = 1 to 1000; do until (x>=0.2); xnew=&scale.*rand("Gamma", &shape.); xold=&scale.*randgam(1,&shape.); end; output; end; run;   proc univariate data=test; var xnew xold; histogram/gamma; inset gamma/pos=ne; run;   The data I'm trying to simulate needs to have a lower bound no less than 0.2, which is why I have the do until loop above. I'm hoping this is appropriate.   Thanks in advance for any help you can provide!         ... View more