Let’s say I’ve generated a posterior distribution for a parameter in a stan regression model, represented by a vector of 30,000 parameter estimates.

I might want to do some work with these posterior estimates that involves a function that is very time consuming to run a large number of times - so might be tricky to do on all 30,000 posterior estimates. If I just wanted to run it on say 1500 samples, would I get a closer representation of the posterior by sampling with, or without, replacement?