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I am not willing to discuss the details on a public forum, especially because my work is unpublished

Understood.

I probably wouldn't understand the hardcore genomics anyway :)

But ... if you could isolate the differences in non-genomic terms. Eg. The results are more random; or less random; or way too random?

Or if you are want to discuss it off-line ...

I am posting about here in this threads, is related to our previous discussion thread on shuffling DNA and using that to estimate False Discovery Rates of a certain type of "feature" in the genome

I thought the processing was familiar :)

One question. Why are you shuffling the data 10 times? Is this your innovation; or part of some procedure described somewhere that you are following?

The reason I ask is: it shouldn't be necessary. Actually, I'll re-state that. It isn't necessary!

The whole point about the Fischer-Yates shuffle is that every possible reordering of the data is possible; and they all have equal probability.

Thus; by shuffling multiple times all you are doing is choosing a different mix. Not a better one; nor a more random one; just a different one.

And that could just as equally be achieved by seeding the PRNG differently: srand( time * rand() ) or similar.

But as all outcomes are possible from every shuffle -- including the first one -- doing multiple shuffles is just wasting time; nothing more.


With the rise and rise of 'Social' network sites: 'Computers are making people easier to use everyday'
Examine what is said, not who speaks -- Silence betokens consent -- Love the truth but pardon error.
"Science is about questioning the status quo. Questioning authority".
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I'm with torvalds on this Agile (and TDD) debunked I told'em LLVM was the way to go. But did they listen!

In reply to Re^3: Random shuffling by BrowserUk
in thread Random shuffling by onlyIDleft

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