Software development for "Bayesian nonparametric population inference". In other words, just the direct application of probability theory to get the most general, principled, model-free inference we can have.
We leave the results of a reference test in some subdirectory within the "tests" directory
Whenever we run a new test, we check that the Fdistribution.rds object from the new test is identical to the old one.
This way we check not only that the scripts are working, but also that their output is consistent with previous versions. I'll modify the testpackage.R script so that it uses the same random seed and make a check against a reference Fdistribution.rds object.
pglpm
commented
1 month ago
I propose that:
Fdistribution.rdsobject from the new test is identical to the old one.This way we check not only that the scripts are working, but also that their output is consistent with previous versions. I'll modify the
testpackage.Rscript so that it uses the same random seed and make a check against a referenceFdistribution.rdsobject.