valTable function

Comparison of different microaggregation methods

A Function for the comparison of different perturbation methods.

valTable(
  x,
  method = c("simple", "onedims", "clustpppca", "addNoise: additive", "swappNum"),
  measure = "mean",
  clustermethod = "clara",
  aggr = 3,
  nc = 8,
  transf = "log",
  p = 15,
  noise = 15,
  w = 1:dim(x)[2],
  delta = 0.1
)

Arguments

• x: a data.frame or a matrix
• method: character vector defining names of microaggregation-, adding-noise or rank swapping 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.
• p: Swapping range, if method swappNum has been chosen
• noise: noise addition, if an addNoise method has been chosen
• w: variables for swapping, if method swappNum has been chosen
• delta: parameter for adding noise method "correlated2"

Returns

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

Details

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

Methods for adding noise should be named via addNoise:{method}, e.g. addNoise:correlated, where {method} specifies the desired method as described in addNoise().

Examples

data(Tarragona)

valTable(
  x = Tarragona[100:200, ],
  method=c("simple", "onedims", "pca")
)

References

Templ, M. and Meindl, B., Software Development for SDC in R, Lecture Notes in Computer Science, Privacy in Statistical Databases, vol. 4302, pp. 347-359, 2006.

See Also

microaggregation(), summary.micro()

Author(s)

Matthias Templ