I have been working on the uncertainty associated with a quantity calculated from a Monte Carlo project. Normally I would use the bootstrap method by resampling with replacement, for a couple of technical reasons that is not particularly easy here. It was suggested that I just break up my MC data set and perform the experiment with these subsets and find the uncertainty that way. I have in the past come across references to bootstrapping with only a subset of the original dataset.
Can someone point me to a tutorial on this or explain briefly how it is different to bootstrapping with replacement and just setting the number of samples to a fraction of the total size. I would be particularly interested in a method that meant that $n$ could be different for each subsample, this would make my analysis much more simple.