|Created: 14 May 2015||Modified: 23 Jul 2020||BibTeX Entry||RIS Citation|
After SAA’s, I used some existing simulations (seriationct-27 from the experiment-seriationct-2 repository) to prototype examining the effects of sample size on:
Working with the existing simulation results and post-processed samples, I wrote a quick modification of the assemblage sampler called
seriationct-sample-assemblages-for-samplesize-sequence-seriation.py. The script takes the output from the
seriationct-export-data.py script and performs subsampling as follows:
samplefractionparameter to select an initial sample of assemblages, just like the normal
sampletypeparameter, as a pure random sample of assemblages, a spatially stratified sample given NxN quadrats, temporally stratified given N even periods of time, and spatiotemporal sampling which stratifies by quadrats and periods.
samplefractionassemblages in a sequence decreasing by 2, so for example, if
samplefractionis 30, the largest set of assemblages will be 30 randomly sampled, and then 28 sampled from the 30, 26 sampled from the original 30, and so on.
The net result is a nested series of samples (rather than independent random samples of different sizes).
Some of the things I want to know are:
I’m just starting to build measures for these items, since they involve traversal and parsing of the annotated minmax graphs.