[R] generate average frame from different data frames

[Luigi Marongiu]

Thanks for the tip! I'll check it out.

On Sun, Oct 24, 2021 at 8:07 AM Jim Lemon <drjimlemon using gmail.com> wrote:
>
> Hi Luigi,
> In that case you will want a binomial confidence interval.
>
> Jim
>
> On Sun, Oct 24, 2021 at 4:39 PM Luigi Marongiu <marongiu.luigi using gmail.com> wrote:
> >
> > 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 <drjimlemon using 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.luigi using 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 using 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



-- 
Best regards,
Luigi