R Under development (unstable) (2024-01-24 r85824 ucrt) -- "Unsuffered Consequences"
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> options(warn=1)
> # ad-hod function for comparing numbers
> qround <- function(x) round(x, dig=3)
> 
> library("compositions")
Welcome to compositions, a package for compositional data analysis.
Find an intro with "? compositions"


Attaching package: 'compositions'

The following objects are masked from 'package:stats':

    anova, cor, cov, dist, var

The following object is masked from 'package:graphics':

    segments

The following objects are masked from 'package:base':

    %*%, norm, scale, scale.default

> set.seed(1334345)
> data(SimulatedAmounts)
> par(pch=20)
> mydata <- simulateMissings(sa.groups5,dl=0.01,knownlimit=TRUE,MAR=0.05,MNARprob=0.05,SZprob=0.05)
> 
> 
> # standard way of creating a compositional dataset
> # (cdata <- acomp(mydata))
> 
> # In this file we suppress unnecessary warnings targeting end-users
> # Human: if you want to see them, replace suppressWarnings() by I()
> cdata <- suppressWarnings( acomp(mydata) )
> suppressWarnings( qround( mean(cdata) ) )
     Cu      Zn      Pb      Cd      Co 
"0.137" "0.650" "0.193" "0.012" "0.007" 
attr(,"class")
[1] "acomp"
> qround( mean(acomp(sa.groups5)) )
     Cu      Zn      Pb      Cd      Co 
"0.142" "0.660" "0.190" "0.005" "0.003" 
attr(,"class")
[1] "acomp"
> plot(acomp(sa.groups5))
> suppressWarnings( plot(mean(cdata),add=T,col="red") )
> plot(mean(acomp(sa.groups5)),add=T,col="green")
> suppressWarnings( qround( mean(cdata - mean(cdata)) ) )
    Cu     Zn     Pb     Cd     Co 
" 0.2" " 0.2" " 0.2" " 0.2" " 0.2" 
attr(,"class")
[1] "acomp"
> 
> mm  <- suppressWarnings( mean(cdata) )
> erg <- suppressWarnings(  var(cdata) )
> 
> print(erg)
           Cu          Zn         Pb          Cd         Co
Cu  1.4584600  1.65184942 -1.3766795 -0.33655679 -1.3970731
Zn  1.6518494  2.68214514 -2.5332217  0.03317017 -1.8339431
Pb -1.3766795 -2.53322167  5.4296947 -2.08907090  0.5692774
Cd -0.3365568  0.03317017 -2.0890709  1.63133485  0.7611227
Co -1.3970731 -1.83394307  0.5692774  0.76112267  1.9006161
> lapply(svd(erg), qround)
$d
[1] 8.412 4.202 0.312 0.176 0.000

$u
       [,1]   [,2]   [,3]   [,4]  [,5]
[1,] -0.308  0.342  0.699 -0.316 0.447
[2,] -0.500  0.337 -0.454  0.481 0.447
[3,]  0.747  0.414 -0.225 -0.142 0.447
[4,] -0.189 -0.541 -0.367 -0.580 0.447
[5,]  0.250 -0.553  0.347  0.558 0.447

$v
       [,1]   [,2]   [,3]   [,4]   [,5]
[1,] -0.308  0.342  0.699 -0.316 -0.447
[2,] -0.500  0.337 -0.454  0.481 -0.447
[3,]  0.747  0.414 -0.225 -0.142 -0.447
[4,] -0.189 -0.541 -0.367 -0.580 -0.447
[5,]  0.250 -0.553  0.347  0.558 -0.447

> 
> ellipses(mm,erg)
> suppressWarnings(
+   ellipses(mean(acomp(sa.groups5)),var(acomp(sa.groups5)))
+   )
> 
> # cdata <- acomp(mydata)
> # plot(cdata)
> suppressWarnings( plot(cdata) )
> suppressWarnings( plot(mm,add=T,col="blue") )
> suppressWarnings( plot(mean(acomp(sa.groups5)),add=T,col="green") )
> suppressWarnings( mean(cdata - mean(cdata)) )
    Cu     Zn     Pb     Cd     Co 
" 0.2" " 0.2" " 0.2" " 0.2" " 0.2" 
attr(,"class")
[1] "acomp"
> # mm <-mean(cdata)
> # erg <-var(cdata)
> # svd(erg)
> suppressWarnings( ellipses(mm,erg) )
> suppressWarnings( ellipses(mm,erg,r=2) )
> 
> 
> 
> #cdata <- rcomp(mydata)
> #cdata
> 
> #mean(cdata)
> #mean(rcomp(sa.groups5))
> #plot(rcomp(sa.groups5))
> #plot(mean(cdata),add=T,col="red",pch=20)
> #plot(mean(rcomp(sa.groups5)),add=T,col="green",pch=20)
> #mean(cdata - mean(cdata)) # Nonsense because the difference is noncompositional
> 
> 
> cdata <- aplus(mydata)
> # cdata
> qround( mean(cdata) )
[1] " 5.969" "26.965" " 8.239" " 0.574" " 0.326"
attr(,"class")
[1] "aplus"
> qround( mean(aplus(sa.groups5)) )
      Cu       Zn       Pb       Cd       Co 
" 6.119" "28.498" " 8.230" " 0.231" " 0.123" 
attr(,"class")
[1] "aplus"
> plot(aplus(sa.groups5))
> plot(mean(cdata),add=T,col="red",pch=20)
> plot(mean(aplus(sa.groups5)),add=T,col="green",pch=20)
> mean(cdata - mean(cdata))
[1] "   1" "   1" "   1" "   1" "   1"
attr(,"class")
[1] "aplus"
> 
> cdata <- rplus(mydata)
> # cdata
> suppressWarnings( qround(  mean(cdata) ) )
[1] " 12.809" "107.744" " 32.008" "  7.252" "  1.039"
attr(,"class")
[1] "rplus"
> qround(  mean(rplus(sa.groups5)) )
       Cu        Zn        Pb        Cd        Co 
" 13.183" "121.516" " 31.863" "  6.997" "  1.399" 
attr(,"class")
[1] "rplus"
> plot(rplus(sa.groups5))
> 
> # Attention: next row should send a warning and produce no result. 
> # Human: uncomment if you want to check that manually
> # plot(mean(cdata),add=T,col="red",pch=20)
> 
> plot(mean(rplus(sa.groups5)),add=T,col="green",pch=20)
> # Attention: next row should send a warning and produce no result
> # Human: uncomment if you want to check that manually
> # mean(cdata - mean(cdata)) # Nonsense because the difference is non compositonal
> 
> 
> suppressWarnings( plot(acomp(mydata)) )
> plot(aplus(mydata))
> suppressWarnings( plot(rcomp(mydata)) )
> plot(rplus(mydata))
> 
> suppressWarnings( boxplot(acomp(mydata)) )
> boxplot(aplus(mydata))
> suppressWarnings( boxplot(rcomp(mydata)) )
> boxplot(rplus(mydata))
> 
> suppressWarnings( barplot(acomp(mydata)) )
> barplot(aplus(mydata))
> suppressWarnings( barplot(rcomp(mydata)) )
> barplot(rplus(mydata))
> 
> proc.time()
   user  system elapsed 
   4.78    0.62    5.39