## data.frame method / all combinations up to maxDim
# riskyCells(
# obj = testdata2,
# keyVars = 1:5,
# threshold = c(50, 25, 10, 5),
# useIdentificationLevel = FALSE,
# maxDim = 4
# )
#riskyCells(
# obj = testdata2,
# keyVars = 1:5,
# threshold = 10,
# useIdentificationLevel = FALSE,
# maxDim = 3
#)
#
### data.frame method / using identification levels
#riskyCells(
# obj = testdata2,
# keyVars = 1:6,
# threshold = 20,
# useIdentificationLevel = TRUE,
# level = c(1, 1, 2, 3, 3, 5)
#)
#riskyCells(
# obj = testdata2,
# keyVars = c(1, 3, 4, 6),
# threshold = 10,
# useIdentificationLevel = TRUE,
# level = c(1, 2, 2, 4)
#)
#
### sdcMicroObj-method / all combinations up to maxDim
#testdata2[1:6] <- lapply(1:6, function(x) {
# testdata2[[x]] <- as.factor(testdata2[[x]])
#})
#
#sdc <- createSdcObj(
# dat = testdata2,
# keyVars = c("urbrur", "roof", "walls", "water", "electcon", "relat", "sex"),
# numVars = c("expend", "income", "savings"),
# w = "sampling_weight")
#
#r0 <- riskyCells(
# obj = sdc,
# useIdentificationLevel=FALSE,
# threshold = c(20, 10, 5),
# maxDim = 3
#)
#
### in case key-variables have been modified, we get counts for
### original and modified data
#sdc <- groupAndRename(
# obj = sdc,
# var = "roof",
# before = c("5", "6", "9"),
# after = "5+"
#)
#r1 <- riskyCells(
# obj = sdc,
# useIdentificationLevel = FALSE,
# threshold = c(10, 5, 3),
# maxDim = 3
#)
#
### sdcMicroObj-method / using identification levels
#riskyCells(
# obj = sdc,
# useIdentificationLevel = TRUE,
# threshold = 10,
# level = c(1, 1, 3, 4, 5, 5, 5)
#)
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