ilr.stab: Compute the Robust ilr Stability for Two Parts of a...

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

View source: R/ilr.stab.R

Description

Function computes the Robust ilr Stability for two parts of a composition following the procedure in Filzmoser et al. (2010), see details below.

Usage

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ilr.stab(xx1, xx2, ifwarn = T)

Arguments

xx1

a column vector from a matrix or data frame of compositional data,
xx1[1], ..., xx1[n].

xx2

another column vector from the matrix or data frame of compositional data, xx2[1], ..., xx2[n]. xx1 and xx2 must be of identical length, n.

ifwarn

by default ifwarn = TRUE which generates a reminder/warning that when carrying out analyses of compositional data all data must be in the same measurement units. The message can be suppressed by setting ifwarn = FALSE.

Details

The ilr transform of two parts of a composition is ilr.xy = 1/(sqrt(2)) * log(x1/x2). The Robust ilr Stability (Filzmoser et al., 2010) is computed from the MAD of the ilr.xy values. This is normalized into the (0,1) interval as exp(-ilr.MAD * ilr.MAD), following the procedure of Buccianti and Pawlowsky-Glahn (2005).

Note

Any less than detection limit values represented by negative values, or zeros or other numeric codes representing blanks in the data, must be removed prior to executing this function, see ltdl.fix.df.

Any data vectors (rows) containing NAs are removed prior to computation.

Author(s)

Robert G. Garrett

References

Buccianti, a. and Pawlowsky-Glahn, V., 2005. New perspectives on water chemistry and compositional data analysis. Mathematical Geology, 37(7):703-727.

Filzmoser, P, Hron, K. and Reimann, C., 2010. The bivariate statistical analysis of environmental (compositional) data. Science of the Total Environment, 408(19):4230-4238.

See Also

ltdl.fix.df, remove.na

Examples

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## Make test data available
data(sind)
attach(sind)

## Compute Robust ilr Stability
ilr.stab(Cu, Zn)

## Detach test data
detach(sind)

rgr documentation built on May 2, 2019, 6:09 a.m.

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