cenLR: Centred logratio coefficients

View source: R/cenLR.R

cenLRR Documentation

Centred logratio coefficients

Description

The centred logratio (clr) coefficients map D-part compositional data from the simplex into a D-dimensional real space.

Usage

cenLR(x, base = exp(1))

Arguments

x

multivariate data, ideally of class data.frame or matrix

base

a positive or complex number: the base with respect to which logarithms are computed. Defaults to exp(1).

Details

Each composition is divided by the geometric mean of its parts before the logarithm is taken.

Value

the resulting clr coefficients, including

x.clr

clr coefficients

gm

the geometric means of the original compositional data.

Note

The resulting data set is singular by definition.

Author(s)

Matthias Templ

References

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

See Also

cenLRinv, addLR, pivotCoord, addLRinv, pivotCoordInv

Examples


data(expenditures)
eclr <- cenLR(expenditures)
inveclr <- cenLRinv(eclr)
head(expenditures)
head(inveclr)
head(pivotCoordInv(eclr$x.clr))


robCompositions documentation built on Aug. 25, 2023, 5:13 p.m.