dimVar
, hierarchies
, or formula
is specified.
dimVar
was automatically generated from the remaining columns.SuppressDominantCells()
and the underlying function MagnitudeRule()
have been improved:
contributorVar
(charVar
) can now be combined with sWeightVar
.protectZeros
. See this parameter's documentation in ?MagnitudeRule
.removeCodesFraction
allows adjustment of the effect of the removeCodes
parameter.apply_abs_directly
determines how negative values are treated in the rules:
apply_abs_directly = FALSE
(default), absolute values are taken after summing
contributions, as performed by max_contribution()
in
the SSBtools package.apply_abs_directly = TRUE
, absolute values are computed directly on the input values,
prior to any summation [beyond preAggregate
]. This corresponds to the old behavior of the function.allDominance = TRUE
:
primary.2:80
((2,80) dominance)) is now dominant2
.allDominance
parameter.MaxContribution()
with the improved
max_contribution()
from
SSBtools.tibble
and data.table
input (parameter data
).
as.data.frame()
where necessary to ensure consistent behavior.preAggregate
is TRUE
and aggregatePackage
is "data.table"
, the use of as.data.frame()
is skipped to avoid unnecessary back-and-forth conversion of data.table
objects, preserving efficiency.GaussSuppressionFromData()
and its wrappers.SSBtools
functions FormulaSelection()
and its identical wrapper formula_selection()
are now re-exported.
library(SSBtools)
is no longer necessary to access them.get_klass()
in the
klassR package
or hier_create()
in the
sdcHierarchies package
can now be used directly as input. Example of usage:
a <- get_klass(classification = "24")
b <- hier_create(root = "Total", nodes = LETTERS[1:5])
mydata <- data.frame(tree = sample(a$code[nchar(a$code) > 1], 200, replace = TRUE),
letter = LETTERS[1:5])
SuppressSmallCounts(mydata, maxN = 3, hierarchies = list(tree = a, letter = b))
map_hierarchies_to_data()
function.Formula2ModelMatrix()
parameter avoidHierarchical = TRUE
,
thanks to the new total_collapse()
function which can be applied to output.NAomit
to SSBtools::Formula2ModelMatrix()
:
TRUE
, NAs in the grouping variables are omitted in output and not included as a separate category.GaussSuppressionFromData()
and its wrappers.aggregateNA
is new parameter to GaussSuppressionFromData()
:
TRUE
(default) to utilize the above NAomit
parameter.aggregatePackage
to "data.table"
to utilize this possibility.
aggregatePackage
is parameter to GaussSuppressionFromData()
and its wrappers.aggregateBaseOrder
and rowGroupsPackage
.remove0
parameter in SuppressFewContributors/NContributorsRule
introduced in version 0.8.0.
When a single numVar
was used as input, the remove0
functionality failed.SuppressDominantCells()
is now considered a common function for both the nk-dominance rule and the p-percent rule.
pPercent
parameter is now exposed in the SuppressDominantCells()
documentation.n
parameter in SuppressDominantCells()
now defaults to 1:length(k)
.
GaussSuppression()
,
"anySum"
in GaussSuppression()
to align with best theory.
singletonMethod
to either "anySumOld"
or "anySumNOTprimaryOld"
.lpPackage
parameter, further suppression will be performed to satisfy the interval width requirements.
rangePercent
: Required interval width expressed as a percentagerangeMin
: Minimum required width of the intervalsingletonMethod = "numttHTT"
, has been introduced in the
wrappers SuppressDominantCells()
and SuppressFewContribitors()
.
This setting represents the method that offers the highest level of protection.
However, it should be noted that with this setting, the computational load of
the suppression algorithm may double, which could potentially lead to a doubling of the
execution time as well. During these computations, ":::" will be displayed instead of "....".
singletonMethod = "numttHtT"
.singletonMethod = "numttH"
.singletonMethod = "numttT"
.singletonMethod = "none"
.?SSBtools::NumSingleton
.SuppressDominantCells()
and SuppressFewContributors()
wrappers.
dominanceVar
and candidatesVar
.removeCodes
parameter is now also available in the DominanceRule()
and SuppressDominantCells()
functions.contributorVar
(charVar
) in the SuppressFewContributors()
and NContributorsRule()
functions.SuppressDominantCells()
includes special functionality to prevent zero cells, which have been suppressed,
from being revealable in cases where negative values cannot occur. See the parameter singletonZeros
.pPercent
parameter directly through SuppressDominantCells()
.PPercentRule()
.
PPercentRule()
and DominanceRule()
now serve as wrappers for the newly introduced.
general function MagnitudeRule()
.AdditionalSuppression()
generalized to take a wrappers as input.PrimaryRemoveWg()
, CandidatesNumWg()
and ForcedWg()
ComputeIntervals()
.lpPackage
parameter is specified in GaussSuppressionFromData()
or in any of its wrappers,
intervals for primary suppressed cells will be computed and included in the output.SuppressDominantCells()
and SuppressFewContributors()
.
extraAggregate = TRUE
in the specs, dominanceSpec
and fewContributorsSpec
.PackageSpecs()
.SuppressSmallCounts()
, SuppressDominantCells()
, and SuppressFewContributors()
,
along with SuppressKDisclosure()
(which was available in the previous version).PackageSpecs()
.DominanceRule()
.SSBtools::GaussSuppression()
.SingletonUniqueContributor()
.forced
and usafe
are possible output columns.
forcedInOutput
and unsafeInOutput
to GaussSuppressionFromData()
.freqVar
and weightVar
, are kept in the output.
"freq"
and "weight"
.freqVar
/weightVar
than "freq"
/"weight"
needs to be updated."freq"
is still default when data is aggregated from microdata without freqVar
specified (see new parameter freqVarNew
).