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Validation of PhEq_bootstrap [Software]

posted by ElMaestro - Denmark, 2018-07-13 10:14  - Posting: # 19043
Views: 751

Hi Hötzi,

» Dokumentation, darling! The file contains not only the four estimates (ƒ1, ƒ2, unbiased ƒ2, ƒ2*) in full precision for the X bootstraps but also the raw data (+average, variance) of all samples. That’s a fucking lot.

Yes, that is a lot. Perhaps a lot of time is spent writing the datasets to file streams and flushing file buffers.

Still, let us say 6 time points, 12 chambers, 2 formulation: ~144 Mb, plus the array of f2*. Allocating that sort of memory should not be an issue ever on newer hardware. The browser you have opened right now to read this post consumes a lot more, probably by a factor 4-10 :-D

What is the use of having all that info cached??

Under bootstrapping the i'th dataset is as valid as the j'th dataset where (i,j) is in ([0;B], [0;B]). When I write resampling code I usually just extract a few dataset and print e.g. the 111'th sample or whatever and check that it has the right set of elements (i.e. that the 111'th dataset (or whatver) for Test only has Test values at the 'right' time points and so forth). And I can check that the derived f2* is one I can reproduce by manual calculation in another application. It isn't such a lot of work. But if I had to do that for a million datasets, then I'd be very, very late for dinner.

What I find little more tricky is to convince myself that the derivation of CI's from the vector of f2* values is valid. A key element here is the sorting. What I did once was to output the sorted first 65536 rows of the sorted array and import them in a spreadsheet (if I recall correctly 65536 is the maximum number of rows in my spreadsheet). Then copy those values to another column, sort this column, and check if row difference exist. A row difference would indicate a sorting mishap in one of the applications. Never observed it, fortunately.

if (3) 4

Best regards,
ElMaestro

"(...) targeted cancer therapies will benefit fewer than 2 percent of the cancer patients they’re aimed at. That reality is often lost on consumers, who are being fed a steady diet of winning anecdotes about miracle cures." New York Times (ed.), June 9, 2018.

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