### Description

In a compositional dataset the relation of two objects can be interpreted safer than a single amount. These functions compute, display and plot the corresponding pair-information for the various principal component analysis results.

### Usage

relativeLoadings(x,...)
## S3 method for class 'princomp.acomp'
cutoff=0.1)
## S3 method for class 'princomp.aplus'
cutoff=0.1)
## S3 method for class 'princomp.rcomp'
cutoff=0.1)
## S3 method for class 'princomp.rplus'
cutoff=0.1)
print(x,...,cutoff=attr(x,"cutoff"),
digits=2)
print(x,...,cutoff=attr(x,"cutoff"),
digits=2)
print(x,...,cutoff=attr(x,"cutoff"),
digits=2)
print(x,...,cutoff=attr(x,"cutoff"),
digits=2)
plot(x,...)
plot(x,...)
plot(x,...)
plot(x,...)


### Arguments

 x a result from an amount PCA princomp.acomp/princomp.aplus/princomp.rcomp/princomp.rplus log a logical indicating to use log-ratios instead of ratios scale.sdev if not NA, a number specifying the multiple of a standard deviation, used to scale the components cutoff a single number. Changes under that (log)-cutoff are not displayed digits the number of digits to be displayed ... further parameters to internally-called functions

### Details

The relative loadings of components allow a direct interpretation of the effects of principal components. For acomp/aplus classes the relation is induced by a ratio, which can optionally be log-transformed. For the rcomp/rplus-classes the relation is induced by a difference, which is meaningless when the units are different.

### Value

The value is a matrix of type "relativeLoadings.princomp.*", containing the ratios in the compositions represented by the loadings (optionally scaled by the standard deviation of the components and scale.sdev).

### Author(s)

K.Gerald v.d. Boogaart http://www.stat.boogaart.de

princomp.acomp, princomp.aplus, princomp.rcomp, princomp.rplus, barplot

### Examples

data(SimulatedAmounts)
pc <- princomp(acomp(sa.lognormals5))
pc
summary(pc)