On Mon, Apr 22, 2013 at 3:48 PM, Lorenzo Isella <lorenzo.ise...@gmail.com> wrote: > Dear All, > I hope this is not too off topic. > I am given a set of scatteplots (nothing too fancy; think about a > normal x-y 2D plot). > I do not deal with two time series (indeed I have no info about time). > If I call A=(A1,A2,...) and B=(B1, B2, ...) the 2 variables (two > vectors of numbers most of the case, but sometimes they can be > categorical variables), I can plot one against the other and I > essentially I need to determine whether > > A=f(B, noise) or B=g(A, noise)
What's the mathematical difference in these two cases? It seems only a matter of interpretation. > > where the noise is the effect of other possibly unknown variables, > measurement errors etc.... and f and g are two functions. > > Without the noise, if I want to test if A=f(B) [B causes A], then I > need at least to ensure that f(B1)!=f(B2) must imply B1!=B2 (different > effects must have a different cause), whereas it is not ruled out that > f(B1)=f(B2) for B1!=B2 (different causes may lead to the same effect). > > However, in presence of the noise, these properties will hold only > approximately Do they even hold approximately? >so....any idea about how a statistical test, rather than > eyeballing, to tell apart A=f(B, noise) vs B=g(A, noise)? > Any suggestion is welcome. http://xkcd.com/552/ > > Lorenzo > > ______________________________________________ > R-help@r-project.org mailing list > 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. ______________________________________________ R-help@r-project.org mailing list 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.
