sdcMicro (version 5.0.2)

dUtility: data utility

Description

IL1s data utility.

Usage

dUtility(obj, ...)

Arguments

obj

original data or object of class sdcMicroObj-class

...

see arguments below

• xmperturbed data

• methodmethod IL1 or eigen. More methods are implemented in summary.micro()

Value

data utility or modified entry for data utility the sdcMicroObj-class.

Details

The standardised distances of the perturbed data values to the original ones are measured. Measure IL1 measures the distances between the original values and the perturbed ones, scaled by the standard deviation. Method ‘eigen’ and ‘robeigen’ compares the eigenvalues and robust eigenvalues form the original data and the perturbed data.

References

for IL1s: see http://vneumann.etse.urv.es/webCrises/publications/isijcr/lncs3050Outlier.pdf,

Templ, M. and Meindl, B., Robust Statistics Meets SDC: New Disclosure Risk Measures for Continuous Microdata Masking, Lecture Notes in Computer Science, Privacy in Statistical Databases, vol. 5262, pp. 113-126, 2008.

See Also

dRisk, dRiskRMD

Examples

# NOT RUN {
data(free1)
free1 <- as.data.frame(free1)
m1 <- microaggregation(free1[, 31:34], method="onedims", aggr=3)
m2 <- microaggregation(free1[, 31:34], method="pca", aggr=3)
dRisk(obj=free1[, 31:34], xm=m1$mx)
dRisk(obj=free1[, 31:34], xm=m2$mx)
dUtility(obj=free1[, 31:34], xm=m1$mx)
dUtility(obj=free1[, 31:34], xm=m2$mx)
data(Tarragona)
x <- Tarragona[, 5:7]
y <- addNoise(x)$xm
dRiskRMD(x, xm=y)
dRisk(x, xm=y)
dUtility(x, xm=y)
dUtility(x, xm=y, method="eigen")
dUtility(x, xm=y, method="robeigen")

## for objects of class sdcMicro:
data(testdata2)
sdc <- createSdcObj(testdata2,
  keyVars=c('urbrur','roof','walls','water','electcon','relat','sex'),
  numVars=c('expend','income','savings'), w='sampling_weight')
## this is already made internally:
## sdc <- dUtility(sdc)
## and already stored in sdc

# }