[R] generate average frame from different data frames

[Jim Lemon]

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
> > >
> > > ______________________________________________
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> > > and provide commented, minimal, self-contained, reproducible code.
>
>
>
> --
> Best regards,
> Luigi