sdcMicro (version 1.2)

valTable: Comparison of different microaggregation methods

Description

A Function for the comparison of different perturbation methods.

Usage

valTable(x, method = c("simple", "single", "onedims", "pca", "pppca", "clustpca", "clustpppca", "mdav"), measure = "mean", clustermethod = "Mclust", aggr = 3, nc = 8, transf = "log")

Arguments

x

data frame or matrix

method

microaggregation methods

measure

FUN for aggregation. Possible values are mean (default), median, trim, onestep.

clustermethod

clustermethod, if a method will need a clustering procedure

aggr

aggregation level (default=3)

nc

number of clusters. Necessary, if a method will need a clustering procedure

transf

Transformation of variables before clustering.

Value

• Measures of information loss splitted for the comparison of different methods.

Details

Tabelarise the output from summary.micro. Will be enhanced to all perturbation methods in future versions.

See Also

microaggregation, summary.micro

Examples

data(Tarragona)
valTable(Tarragona[100:200,], method=c("simple","onedims","pca","clustpppca"))
## valTable(Tarragona, method=c("simple","onedims","pca","clustpppca","mdav"))
## clustpppca outperforms the other algorithms for this data set...