Measures of information loss splitted for the comparison of different methods.
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"
Author
Matthias Templ
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().
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.