gx.vm: Display an Aitchison Variation Matrix for Compositional Data

In rgr: Applied Geochemistry EDA

Description

The function computes and displays an Aitchison Variation Matrix, with the variances and means of the log-ratios in the upper and lower triangles, respectively.

Usage

gx.vm(xx, ifwarn = TRUE)

Arguments

xx	a matrix, or sub-matrix, of parts from a compositional data set.
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.

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.

Note

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

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

This function is for used with closed compositional data sets, i.e. geochemical analyses. For an alternate approach see gx.sm, where a robust ilr stability measure (Filzmoser et al., 2010) is used rather that the log-ratio variance, and the median of log-ratios is used rather than the mean.

Author(s)

Robert G. Garrett

References

Aitchison, J., 1984. The statistical analysis of geochemical compositions. Mathematical Geology, 16(6):531-564.

Aitchison, J., 1986. Ths Statistical Analysis of Compositional data. Chapman and Hall, London, U.K., 416 p.

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, gx.sm

Examples

 
## Make test data available
data(sind.mat2open)

## Compute Aitchison Variation Matrix
gx.vm(sind.mat2open)

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