Paul A. Bristow wrote:
ons...
General relations: 1) quantile(cdf(x)) == x 2) hazard(x) = pdf(x)/(1-cdf(x)) 3) pdf(x,location,scale) = pdf( (x-location)/scale, 0, 1)/scale 4) cdf(x,location,scale) = cdf( (x-location)/scale, 0, 1) 5) cdf(complement(N,x)) = cdf(N(-x)) 6) quantile(complement(N,p)) = quantile(N(-x,1-p))
perhaps some automatic checking (for all distribution) of error throwing 7) support <-> cdf, pdf 8) quantile <-> p=0, p=1
And some generic test for distributions with specific properties Symmetric distributions: pdf(x) = pdf(-x) cdf(x) = 1-cdf(-x)
etc. we could write template functions for that, that get passed a set of 'x'
values etc
That would indeed be neat - but our tests just grew like Topsy ;-)
And it would be quite a lot of work to change now.
Yes, the use of standardizing testing or all depends on the number of developers. It the numbers grows then at some point it might be a good idea to document a list of tests that are needed. Currently I'll doing fine iterating & growing the test based on feedback from you two. A friend of mine has written a python script to automatically generate 'binding' headers from lapac source. Perhaps at some point it would be doable to automate a lot of that work, but the relevance is low. Cheers, This files