Thank you. Sorry for the fuzziness of the question but I find it difficult to give a proper definition of the problem. I have given a graphical rendering on this post https://www.researchgate.net/post/How_to_find_95_CI_of_a_matrix_of_classification_data As you can see in the figure, there are dots where the same value is represented all the time, and others where the values fluctuate. I would like to generate the "mean" merge of the figures. (Perhaps also with lines saying: this value comes out 9/10 of times, this 5/10 of times...). The problem is that the Z values are factors, not numbers.
On Sun, Oct 24, 2021 at 12:08 AM Jim Lemon <drjimle...@gmail.com> wrote: > > Hi Luigi, > I may be missing the point, but: > > matrix((z1+z2+z3)/3,ncol=10) > > gives you the mean rating for each item, and depending upon what > distribution you choose, the confidence intervals could be calculated > in much the same way. > > Jim > > On Sun, Oct 24, 2021 at 7:16 AM Luigi Marongiu <marongiu.lu...@gmail.com> > wrote: > > > > Hello, > > I have a series of classifications of the same data. I saved this > > classification in a single dataframe (but it could be a list). X and Y > > are the variable and Z is the classification by three raters. `I` is > > the individual identifier of each entry: > > ``` > > z1 = c(0,0,0,0,0,1,0,0,0,2, > > 0,1,1,1,0,0,0,1,0,2, > > 0,1,1,2,0,0,0,1,0,2, > > 1,1,1,2,1,0,0,1,1,2, > > 1,0,0,2,1,1,0,1,2,0) > > z2 = c(0,0,0,0,0,1,0,0,1,1, > > 0,1,1,2,0,0,0,1,1,2, > > 0,0,0,1,0,0,0,1,0,0, > > 1,2,1,2,1,0,0,1,1,2, > > 1,0,1,2,1,1,0,1,2,0) > > z3 = c(0,0,0,2,0,0,0,0,0,2, > > 0,1,0,2,0,0,0,1,0,2, > > 0,1,1,2,0,0,0,1,0,2, > > 1,1,1,2,1,0,0,2,1,2, > > 2,0,1,1,1,1,0,1,1,0) > > df = data.frame(X=rep(1:5,3), Y=rep(1:5,3), Z=factor(c(z1,z2,z3)), I =1:150) > > ``` > > Is there a way to obtain a kind of heath map for each point? Let's say > > for the point (x=1,y-1), what was the most common (average) > > classification? Is it possible to get the 95% CI of that mean? > > Would Two-Dimensional Kernel Density Estimation be the right path? > > Thank you > > > > ______________________________________________ > > 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. -- Best regards, Luigi ______________________________________________ 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.