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.hard...@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. > > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.