plot.acomp {compositions}R Documentation

Displaying compositions in ternary diagrams

Usage

 ## S3 method for class 'acomp':
 plot(x,...,labels=colnames(X),cn=colnames(X),
          aspanel=FALSE,id=FALSE,idlabs=NULL,idcol=2,center=FALSE,
          scale=FALSE,pca=FALSE,col.pca=par("col"),margin="acomp",
          add=FALSE,triangle=!add,col=par("col"))
 ## S3 method for class 'rcomp':
 plot(x,...,labels=colnames(X),cn=colnames(X),
          aspanel=FALSE,id=FALSE,idlabs=NULL,idcol=2,center=FALSE,
          scale=FALSE,pca=FALSE,col.pca=par("col"),margin="rcomp",
          add=FALSE,col=par("col"))
          

Arguments

x a dataset of a compositional class
... further graphical parameters passed (see par)
margin the type of marginalisation to be computed, when displaying the individual panels. Possible values are: "acomp", "rcomp" and any of the variable names/column numbers in the composition. If one of the columns is selected each panel displays a subcomposition given by the row part, the column part and the given part. If one of the classes is given the corresponding margin acompmargin or rcompmargin is used.
add a logical indicating whether the information should just be added to an existing plot. If FALSE a new plot is created
triangle a logical indicating whether the triangle should be drawn
col the color to plot the data
labels the names of the parts
cn the names of the parts to be used in a single panel. Internal use only.
aspanel logical indicating that only a single panel should be drawn and not the whole plot. Internal use only
id logical, if TRUE one can identify the points like with the identify command.
idlabs a character vector providing the labels to be used with the identification, when id=TRUE
idcol color of the idlabs labels
center a logical indicating whether a the data should be centered prior to the plot. Centering is done in the choosen geometry. See scale
scale a logical indicating whether a the data should be scaled prior to the plot. Scaling is done in the choosen geometry. See scale
pca a logical indicating whether the first principal component should be displayed in the plot. Currently, the direction of the principal component of the displayed subcomposition is displayed as a line. In a future, the projected principal componenent of the whole dataset should be displayed.
col.pca The color to draw the principal component.

Details

The data is displayed in ternary diagrams. Thus, it does not work for two-part compositions. Compositions of three parts are displayed in a single ternary diagram. For compositions of more than three components, the data is arranged in a scatterplot matrix through the command pairs.
In this case, the third component in each of the panels is chosen according to setting of margin=. Possible values of margin= are: "acomp", "rcomp" and any of the variable names/column numbers in the composition. If one of the columns is selected each panel displays a subcomposition given by the row part, the column part and the given part. If one of the classes is given the corresponding margin acompmargin or rcompmargin is used.
Ternary diagrams can be read in multiple ways. Each corner of the triangle corresponds to an extreme composition containing only the part displayed in that corner. Points on the edges correspond to compositions containing only the parts in the adjacent corners. The relative amounts are displayed by the distance to the opposite corner (so-called barycentric coordinates). The individual portions of any point can be infered by drawing a line through the investigated point, and parallel to the edge opposite to the corner of the part of interest. The portion of this part is constant along the line. Thus we can read it on the sides of the ternary diagram, where the line crosses its borders. Note that these isoPortionLines remain straight under an arbitrary perturbation.

Author(s)

K.Gerald v.d. Boogaart http://www.stat.boogaart.de, Raimon Tolosana-Delgado

References

Aitchison, J. (1986) The Statistical Analysis of Compositional Data Monographs on Statistics and Applied Probability. Chapman & Hall Ltd., London (UK). 416p.

Aitchison, J, C. Barcel'o-Vidal, J.J. Egozcue, V. Pawlowsky-Glahn (2002) A consise guide to the algebraic geometric structure of the simplex, the sample space for compositional data analysis, Terra Nostra, Schriften der Alfred Wegener-Stiftung, 03/2003

Billheimer, D., P. Guttorp, W.F. and Fagan (2001) Statistical interpretation of species composition, Journal of the American Statistical Association, 96 (456), 1205-1214

Pawlowsky-Glahn, V. and J.J. Egozcue (2001) Geometric approach to statistical analysis on the simplex. SERRA 15(5), 384-398

http://ima.udg.es/Activitats/CoDaWork03

http://ima.udg.es/Activitats/CoDaWork05

See Also

plot.aplus, kingTetrahedron (for 3D-plot), qqnorm.acomp,boxplot.acomp

Examples

data(SimulatedAmounts)
plot(acomp(sa.lognormals))
plot(rcomp(sa.lognormals))
plot(acomp(sa.lognormals5),pca=TRUE)
plot(rcomp(sa.lognormals5),pca=TRUE)

[Package compositions version 0.91-6 Index]