On Mon, 4 Aug 2008, Stephan Neuhaus wrote:
> Or better still, make many tests and see if your p-values are
> uniformly distributed in (0,1). [Hint: decide on a p-value for that
> last equidistribution test *before* you compute that p-value.]
Of course, there are many tests for goodness of fit (Kol
On Aug 3, 2008, at 13:54, Alexander Klimov wrote:
If your p-value is smaller than the significance level (say, 1%)
you should repeat the test with different data and see if the
test persistently fails or it was just a fluke.
Or better still, make many tests and see if your p-values are
unif
On Thu, 31 Jul 2008, Pierre-Evariste Dagand wrote:
> Just by curiosity, I ran the Diehard tests[...]
>
> Sum-up for /dev/random:
> "Abnormally" high value: 0.993189 [1]
> "Abnormally" low value: 0.010507 [1]
> Total: 2
>
> Sum up for Sha1(n):
> "Abnormally" high values: 0.938376, 0.927501 [2]
> "Ab
