[R] normality testing with nortest
Uwe Ligges
ligges at statistik.uni-dortmund.de
Mon May 22 10:16:03 CEST 2006
Raymond Wan wrote:
>
> On Mon, 22 May 2006, Uwe Ligges wrote:
>
>> Rolf Turner wrote:
>>
>>> If the nortest package does it differently (and I don't really see
>>> how it possibly could!) then it is confusingly designed. I rather
>>> suspect that its design is just fine, and that it does what it should
>>> do.
>>
>> I suspect so as well.
>> If you think something is wrong, please contact the package maintainer
>> (CCing; he's not reading R-help posts).
>
>
> Ah, ok -- but in this case, it was clearly my misunderstanding which
> is one reason why I never though of writing to the package maintainer.
> I have one of the books that the Nortest documentation cites, but I was
> clearly reading it backwards or upside-down or something as I missed
> several crucial points.
>
> One thing that threw me off (and this is not really specific to
> Nortest as it seems to be correct, but just my understanding), but the
> p-value seems quite unstable. For example:
>
>> ad.test(rnorm(100,mean=5,sd=3))
>
> ...
> A = 0.2382, p-value = 0.7767
>
>> ad.test(rnorm(100,mean=5,sd=3))
>
> ...
> A = 0.1846, p-value = 0.9059
>
>> ad.test(rnorm(100,mean=5,sd=3))
>
> ...
> A = 0.5138, p-value = 0.1887
>
> I mistakenly had thought the p-values would be more stable since I
> am artificially creating a random normal distribution. Is this expected
> for a normality test or is this an issue with how rnorm is producing
> random numbers? I guess if I run it many times, I would find that I
> would get many large values for the p-value?
Well, as many large values as small values, 5% significant differences
for the 5% level....
The following looks alright:
hist(replicate(1000, ad.test(rnorm(100,mean=5,sd=3))$p.value))
> Ray
>
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