pairwisePlot: Creates a paneled plot like pairs for two different datasets.

In compositions: Compositional Data Analysis

Creates a paneled plot like pairs for two different datasets.

Description

Creates a plot for each element of two lists or each column of each dataset against each of the second.

Usage

pairwisePlot(X,Y,...)
## Default S3 method:
pairwisePlot(X,Y=X,...,
                xlab=deparse(substitute(X)),ylab=deparse(substitute(Y)),
                nm=c(length(Y),length(X)),panel=plot,
                add.line=FALSE, line.col=2,add.robust=FALSE,rob.col=4)

Arguments

X	a list, a data.frame, or a matrix representing the first set of things to be displayed.
Y	a list, a data.frame, or a matrix representing the second set of things to be displayed.
...	furter parameters to the panel function
xlab	The sequence of labels for the elements of X. Alternatively the labels can be given as colnames or names of X. This option takes precedence if specified.
ylab	The sequence of labels for the elements of Y. Alternatively the labels can be given as colnames or names of Y. This option takes precedence if specified.
nm	the parameter to be used in the call par(mfrow=nm). If NULL no parameter is setted and a sequence of plots can be generated.
panel	The panel function to plot the individual panels. If the panel function admits a formula interface, it is called as panel(y~x, xlab=xlab,ylab=ylab,...), otherwise as panel(x, y,xlab=xlab,ylab=ylab,...). Thus the panel function must be capable of taking these arguments. It must also set up its own plot. There is no negotiation on coordinate system.
add.line	logical, to control the addition of a regression line in each panel
line.col	in case the regression line is added, which color should be used? defaults to red.
add.robust	logical, to control the addition of a robust regression line in each panel. Ignored if covariable is a factor. This is nowadays based on lmrob, but this can change in the future.
rob.col	in case the robust regression line is added, which color should be used? Defaults to blue.

Details

This is a light-weight convenience function to plot several aspects of one dataset against several aspects of another dataset. It is far more straight-forward than e.g. the pairs function and does not do any internal computation rather than organizing the names. Of course, the rows of the two data sets must be the same.

The current implementation may display a warning about the function panel dispatching methods for generic plot. It can be ignored without harm.

Optionally, classical and/or robust regression lines can be drawn, though only for non-factor covariables.

It may be convenient to use par capabilities to fit the device characteristics to the plot, in particular arguments mar and oma.

Author(s)

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

References

Boogaart, K.G. v.d. , R. Tolosana (2008) Mixing Compositions and Other scales, Proceedings of CodaWork 08.

https://ima.udg.edu/Activitats/CoDaWork03/

https://ima.udg.edu/Activitats/CoDaWork05/

https://ima.udg.edu/Activitats/CoDaWork08/

See Also

plot.aplus, balance, pwlrPlot

Examples

X <- rnorm(100)
Y <- rnorm.acomp(100,acomp(c(A=1,B=1,C=1)),0.1*diag(3))+acomp(t(outer(c(0.2,0.3,0.4),X,"^")))

pairs(cbind(ilr(Y),X),panel=function(x,y,...) {points(x,y,...);abline(lm(y~x))})
pairs(cbind(balance(Y,~A/B/C),X),
         panel=function(x,y,...) {points(x,y,...);abline(lm(y~x))})
pairwisePlot(balance(Y,~A/B/C),X)
pairwisePlot(X,balance(Y,~A/B/C),
         panel=function(x,y,...) {plot(x,y,...);abline(lm(y~x))})
pairwisePlot(X,balance01(Y,~A/B/C))

# A function to extract a portion representation of subcompsitions
# with two elements:
subComps <- function(X,...,all=list(...)) {
  X <- oneOrDataset(X)
  nams <- sapply(all,function(x) paste(x[[2]],x[[3]],sep=","))
  val  <- sapply(all,function(x){ 
             a = X[,match(as.character(x[[2]]),colnames(X)) ]
             b = X[,match(as.character(x[[2]]),colnames(X)) ]
             c = X[,match(as.character(x[[3]]),colnames(X)) ]
             return(a/(b+c))
           })
  colnames(val)<-nams
  val
}

pairwisePlot(X,subComps(Y,A~B,A~C,B~C))

## using Hydrochemical data set as illustration of mixed possibilities
data(Hydrochem)
xc = acomp(Hydrochem[,c("Ca","Mg","Na","K")])
fk = Hydrochem$River
pH = -log10(Hydrochem$H)
covars = data.frame(pH, River=fk)
pairwisePlot(clr(xc), pH)
pairwisePlot(clr(xc), pH, col=fk)
pairwisePlot(pH, ilr(xc), add.line=TRUE)
pairwisePlot(covars, ilr(xc), add.line=TRUE, line.col="magenta")
pairwisePlot(clr(xc), covars, add.robust=TRUE)

compositions documentation built on June 22, 2024, 12:15 p.m.