[R] ks.test ; impossible to calculate exact exact value with ex-aequos

Fatma Ell f@tm@@m@ci @ending from gm@il@com
Tue Dec 11 00:36:38 CET 2018


Thanks a lot for this reply

'a' is a simulated data while 'b' is empirical data.
Other than correlation, how to check ressemblence between these two curve
in terms of :
Amplitude in each row 1...12
Evolution and variability from 1 to 12

Thanks !


Le lundi 10 décembre 2018, Ted Harding <ted.harding using wlandres.net> a écrit :

> On Mon, 2018-12-10 at 22:17 +0100, Fatma Ell wrote:
> > Dear all,
> > I'm trying to use ks.test in order to compare two curve. I've 0 values i
> > think this is why I have the follonwing warnings :impossible to calculate
> > exact exact value with  ex-aequos
> >
> > a=c(3.02040816326531, 7.95918367346939, 10.6162790697674,
> 4.64150943396226,
> > 1.86538461538462, 1.125, 1.01020408163265, 1.2093023255814,
> > 0.292452830188679,
> > 0, 0, 0)
> > b=c(2.30769230769231, 4.19252873563218, 5.81924882629108,
> 6.2248243559719,
> > 5.02682926829268, 4.50728862973761, 3.61741424802111, 5.05479452054795,
> > 3.68095238095238, 1.875, 5.25, 0)
> >
> > ks.test(a,b)
> >
> > data:  a and b
> > D = 0.58333, p-value = 0.0337
> > alternative hypothesis: two-sided
> >
> > Warning message:
> > In ks.test(a, b) :
> > impossible to calculate exact exact value with ex-aequos
> >
> > Does the p-value is correct ? Otherwise, how to solve this issue ?
> > Thanks a lot.
>
> The warning arises, not because you have "0" values as such,
> but because there are repeated values (which happen to be 0).
>
> The K-S test is designed for continuous random variables, for
> which the probability of repeated values is (theoretically) zero:
> theoretically, they can't happen.
>
> >From the help page ?ks.test :
>
> "The presence of ties always generates a warning, since continuous
> distributions do not generate them. If the ties arose from
> rounding the tests may be approximately valid, but even modest
> amounts of rounding can have a significant effect on the
> calculated statistic."
>
>
>
> in view of the fact that your sample 'a' has three zeros along with
> nine other vauwes which are all different from 0 (and all *very*
> different from 0 except for 0.292452830188679), along with the fact
> that your sample 'b' has 11 values all *very* different from 0.
> and pne finall value equal to 0; together also with the fact that
> in each sample the '0' values occur at the end, stringly suggests
> that the data source is not such that a K-D test is auitasble.
>
> The K-S test is a non-parametric test for whether
>   a) a given sample comes from na given kind of distribiution;
> or
>   v) two samples are drwn from the same distribition.
> In either case, it is assumed that the sample values are drawn
> independently of each other; if there is some reason why they
> may not be independent of each other, the test os not valid.
>
> You say "I'm trying to use ks.test in order to compare two curve".
> When I ezecute
>   plot(a)
>   plot(b)
> on your data, I see (approximately) in each case a rise from a
> medium vale (~2 or ~3) to a higher vale {~6 or ~10) followed
> by a decline down to an exact 0.
>
> This is not the sort of situation that the K-S test is for!
> Hoping this helps,
> Ted.
>
>

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