mun_accidents <- SSBtoolsData("mun_accidents")
SuppressSmallCounts(data = mun_accidents, maxN = 3, dimVar = 1:2, freqVar = 3)
# override default spec
SuppressSmallCounts(data = mun_accidents, maxN = 3, dimVar = 1:2, freqVar = 3,
protectZeros = FALSE)
d2 <- SSBtoolsData("d2")
d2$f <- round(d2$freq/10) # tenth as frequency in examples
# Hierarchical region variables are detected automatically -> same output column
SuppressSmallCounts(data = d2, maxN = 2, freqVar = "f",
dimVar = c("region", "county", "k_group"))
# Formula. Hierarchical variables still detected automatically.
SuppressSmallCounts(data = d2, maxN = 3, freqVar = "f",
formula = ~main_income * k_group + region + county - k_group)
# With hierarchies created manually
ml <- data.frame(levels = c("@", "@@", "@@@", "@@@", "@@@", "@@"),
codes = c("Total", "not_assistance", "other", "pensions", "wages", "assistance"))
SuppressSmallCounts(data = d2, maxN = 2, freqVar = "f",
hierarchies = list(main_income = ml, k_group = "Total_Norway"))
# Data without pensions in k_group 400
# And assume these are structural zeros (will not be suppressed)
SuppressSmallCounts(data = d2[1:41, ], maxN = 3, freqVar = "f",
hierarchies = list(main_income = ml, k_group = "Total_Norway"),
extend0 = FALSE, structuralEmpty = TRUE)
# -- Note for the example above --
# With protectZeros = FALSE
# - No zeros suppressed
# With extend0 = FALSE and structuralEmpty = FALSE
# - Primary suppression without protection (with warning)
# With extend0 = TRUE and structuralEmpty = TRUE
# - As default behavior. Suppression/protection of all zeros (since nothing empty)
# With formula instead of hierarchies: Extra parameter needed when extend0 = FALSE.
# - removeEmpty = FALSE, to include empty zeros in output.
# Using formula followed by FormulaSelection
output <- SuppressSmallCounts(data = SSBtoolsData("example1"),
formula = ~age * geo * year + eu * year,
freqVar = "freq",
maxN = 1)
FormulaSelection(output, ~(age + eu) * year)
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