primarySuppression: perform primary suppression in `sdcProblem-class`-objects

Description

Function primarySuppression is used to identify and suppress primary sensitive table cells in sdcProblem-class objects. Argument type allows to select a rule that should be used to identify primary sensitive cells. At the moment it is possible to identify and suppress sensitive table cells using the frequency-rule, the nk-dominance rule and the p-percent rule.

Usage

primarySuppression(object, type, ...)

Arguments

object

a sdcProblem-class object

type

character vector of length 1 defining the primary suppression rule. Allowed types are:

freq: apply frequency rule with parametersmaxNandallowZeros
nk: apply nk-dominance rule with p

...

parameters used in the identification of primary sensitive cells. Parameters that can be modified|changed are:

maxN: numeric vector of length 1 used when applying the frequency rule. All cells having counts <=maxN

`Value`

a sdcProblem-class object

`Examples`

Run this code# load micro data
sp <- searchpaths()
fn <- paste(sp[grep("sdcTable", sp)], "/data/microData1.RData", sep="")
microData <- get(load(fn))

# load problem (as it was created in the example in \code{\link{makeProblem}})
fn <- paste(sp[grep("sdcTable", sp)], "/data/problem.RData", sep="")
problem <- get(load(fn))

# we have a look at the table
print(table(microData))

# cell with region=='A' and gender=='female' has 2 units contributing to it
# this cell should be considered senstive!
problem <- primarySuppression(problem, type='freq', maxN=3)

# looking at anonymization states
print(table(getInfo(problem, type='sdcStatus')))

# we see that exactly one cell is primary suppressed (sdcStatus=='u') and
# the remaining cells are possible candidates for secondary suppression ('s')
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