compositions (version 0.9-11)

var.acomp: Variances and covariances of amounts and compositions

Description

Compute the (co)variance matrix in the several approaches of compositional and amount data analysis.

Usage

var(x,...)
          ## S3 method for class 'default':
var(x, y=NULL, na.rm=FALSE, use, \dots)
          ## S3 method for class 'acomp':
var(x,y=NULL,\dots)
          ## S3 method for class 'rcomp':
var(x,y=NULL,\dots)
          ## S3 method for class 'aplus':
var(x,y=NULL,\dots)
          ## S3 method for class 'rplus':
var(x,y=NULL,\dots)
          ## S3 method for class 'rmult':
var(x,y=NULL,\dots)
          cov(x,y=x,...)
          ## S3 method for class 'default':
cov(x, y=NULL, use="all.obs", method=c("pearson",
    "kendall", "spearman"), ...)
          ## S3 method for class 'acomp':
cov(x,y=NULL,\dots)
          ## S3 method for class 'rcomp':
cov(x,y=NULL,\dots)
          ## S3 method for class 'aplus':
cov(x,y=NULL,\dots)
          ## S3 method for class 'rplus':
cov(x,y=NULL,\dots)
          ## S3 method for class 'rmult':
cov(x,y=NULL,\dots)

Arguments

x

a dataset, eventually of amounts or compositions

y

a second dataset, eventually of amounts or compositions

na.rm

see var

use

see var

method

see cov

...

further arguments to var e.g. use

Value

• The variance matrix of x or the covariance matrix of x and y.

Details

The basic functions of var, cov are turned to S3-generics. The original versions are copied to the default method. This allows us to introduce generic methods to handle variances and covariances of other datatypes such as amounts or compositions. If classed amounts or compositions are involved, they are transformed with their corresponding transforms, using the centered default transform (cdt). That implies that the variances have to be interpreded in a log scale level for acomp and aplus. We should be aware that variance matrices of compositions are singular. They can be transformed to the correponding nonsingular variances of ilr or ipt -space by clrvar2ilr.

In R versions older than v2.0.0, var and cov were defined in package ``base'' instead of in ``stats''. This might produce some misfunction.

See Also

cdt, clrvar2ilr, clo, mean.acomp, acomp, rcomp, aplus, rplus, variation

Examples

data(SimulatedAmounts)
mean.col(sa.lognormals)
var(acomp(sa.lognormals))
var(rcomp(sa.lognormals))
var(aplus(sa.lognormals))
var(rplus(sa.lognormals))
cov(acomp(sa.lognormals5[,1:3]),acomp(sa.lognormals5[,4:5]))
cov(rcomp(sa.lognormals5[,1:3]),rcomp(sa.lognormals5[,4:5]))
cov(aplus(sa.lognormals5[,1:3]),aplus(sa.lognormals5[,4:5]))
cov(rplus(sa.lognormals5[,1:3]),rplus(sa.lognormals5[,4:5]))
cov(acomp(sa.lognormals5[,1:3]),aplus(sa.lognormals5[,4:5]))

svd(var(acomp(sa.lognormals)))