sdcTable (version 0.6.4)

protectTable: protectTable

Description

....

Usage

protectTable(outObj, method, ...)

Arguments

outObj

a list-object generated by calcFullTable() and possibly changed by primarySuppression().

method

the protection algorithmus. Currently 'OPT', 'HITAS' and 'HYPERCUBE' are possible choices

...

additional parameters depending on the choice of the suppression algorithm. If 'HYPERCUBE' is used, it is possible to use parameter 'suppMethod' with possible choices 'minSupps' (suppress cubes with minimal number of secondary suppressions),'minSum' (min

Value

• an object of class 'safeTable'

References

Repsilber, D. (1999). Das Quaderverfahren. In: Forum der Bundesstatistik, Band 31/1999. de Wolf, P.P (2002). HiTaS: A Heuristic Approach to Cell Suppression in Hierarchical Tables. In: Domingo-Ferrer, J. (Hrsg.): Inference Control in Statistical Databases. Vol. 2316. Fischetti, M., Salazar, J.J. (2000). Models and Algorithms for Optimizing Cell Suppression in Tabular Data with Linear Constraints. In: Journal of the American Statistical Association 95, 916-928.

Examples

# generate micro-data
N <- 2500
set.seed(123)
V1 <- sample(c("011","012","013","021","022"), N, replace=TRUE)
V2 <- sample(c("m","w"), N, replace=TRUE)
V3 <- sample(c("01","02"), N, replace=TRUE)
V4 <- sample(c("Aa","Ab", "Ac","Ba","Ca","Da","Db", "Ea","Fa","Fb",
"Ga","Gb","Ha","Ia","Ja","Jb","Ka","Kb"), N, replace=TRUE)
	
microDat <- data.frame(V1=V1,V2=V2,V3=V3,V4=V4)
microDat$numVal <- abs(round(rnorm(N, 500, 200),2))
sInd <- sample(floor(N/20))
microDat$numVal[sInd] <- abs(round(rnorm(sInd, 100000, 200),2))
	
# dimension 1
h1 <- c("@@", "@@@","@@@","@@@","@@", "@@@","@@@")
l1 <- c("010", "011", "012","013","020", "021","022")
df1 <- data.frame(h=h1, l=l1)
hier1 <- calcDimInfos(microDat, file=NULL, dataframe=df1, vName="V1") 

# Level 2
h2 <- c("@@", "@@")
l2 <- c("m", "w")
df2 <- data.frame(h=h2, l=l2)
hier2 <- calcDimInfos(microDat, file=NULL, dataframe=df2, vName="V2") 

# Level 3
h3 <- c("@@", "@@")
l3 <- c("A", "B")
df3 <- data.frame(h=h3, l=l3)
hier3 <- calcDimInfos(microDat, file=NULL, dataframe=df3, vName="V3") 

# Level 4
h4 <- c("@@","@@@","@@@","@@@","@@","@@@","@@","@@@","@@","@@@","@@@",
		"@@","@@@","@@","@@@","@@@","@@","@@@","@@@","@@","@@@",
		"@@","@@@","@@","@@@","@@@","@@","@@@","@@@") 
l4 <- c("A","Aa","Ab","Ac","B","Ba","C","Ca","D","Da","Db",
		"E","Ea","F","Fa","Fb","G","Ga","Gb","H","Ha",
		"I","Ia","J","Ja","Jb","K","Ka","Kb")
df4 <- data.frame(h=h4, l=l4)
hier4 <- calcDimInfos(microDat, file=NULL, dataframe=df4, vName="V4") 

# the complete levelObject
levelObj <- list(hier1, hier2, hier3, hier4)	

outObj <- calcFullTable(microDat, levelObj, numVar="numVal")
outObj <- primarySuppression(outObj, suppRule_Freq=c(3,0))

LPL <- rep(1, length(outObj$fullTabObj$strID)) # non negative
UPL <- rep(1, length(outObj$fullTabObj$strID)) # non negative
SPL <- rep(0, length(outObj$fullTabObj$strID)) # non negative

outObj <- setBounds(outObj, type="UPL", UPL)
outObj <- setBounds(outObj, type="LPL", LPL)
outObj <- setBounds(outObj, type="SPL", SPL)				
outHITAS <- protectTable(outObj, solver="glpk", method="HITAS")
print(str(outHITAS))