Hello,
That is a warning, not an error.
And it documented. In ?ks.test, section Details, the relevant part is
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.
It then adds, three paragraphs down:
Exact p-values are not available for the two-sample case if one-sided or
in the presence of ties.
You can use exact = FALSE but it will still issue a warning.
ks.test(a, b, exact = FALSE)
Two-sample Kolmogorov-Smirnov test
data: a and b
D = 0.58333, p-value = 0.0337
alternative hypothesis: two-sided
Warning message:
In ks.test(a, b, exact = FALSE) :
p-value will be approximate in the presence of ties
Hope this helps,
Rui Barradas
Às 21:17 de 10/12/2018, Fatma Ell escreveu:
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.
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