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Oh, something I forgot to mention: I tried using a constant number of bits but varying the vector size/quantity to see how things scaled. In other words, I compared:

vec size# vectors
10,000 1
5,000 2
3,333 3
2,500 4
2,000 5
1,00010

I found more smaller vectors works better until the number of samples matches the number if bits in the smaller vector. Plotting the functions:

(1-exp(-x/1000))^10 (1-exp(-x/2000))^5 (1-exp(-x/2500))^4 (1-exp(-x/3333))^3 1-exp(-x/10000)

using a graphing calculator shows that's where the curves cross:

...roboticus

When your only tool is a hammer, all problems look like your thumb.


In reply to Re^2: [OT] The statistics of hashing. by roboticus
in thread [OT] The statistics of hashing. by BrowserUk

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