cenLR: Centred logratio coefficients

Description Usage Arguments Details Value Note Author(s) References See Also Examples

View source: R/cenLR.R

Description

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

Usage

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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 \& Hall Ltd., London (UK). 416p.

See Also

cenLRinv, addLR, pivotCoord, addLRinv, pivotCoordInv

Examples

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

robCompositions documentation built on Jan. 13, 2021, 10:07 p.m.