by calling unclass(data.fit) you can see all the parts that make up the data.fit object, which include: $estimate mean sd 0.1125554 1.2724377 which means you can access the estimated mean and standard deviation via: data.fit$estimate['sd'] data.fit$estimate['mean'] To calculate the upper 5th percentile of the fitted distribution, you can use the...

It may be informative for users to know that I finally solved this with what turned out to be a simple solution (with help from a friend). Since exp(a+b) = exp(a)*exp(b), the equation can be rewritten: Weight ~ I(A/(1+((A/1.022)-1) * exp(v0*Age + v1*Sum.T)) Which fits without any problems. In general,...

sas,model-fitting,goodness-of-fit

I do not have access to SAS/ETS so cannot confirm this with proc severity, but I imagine that the difference you are seeing come down to the way the distribution parameters are fitted. With your proc univriate code you are not requesting estimation for several of the parameters (some are...