Changelog

Source: NEWS.md

GaussSuppression 0.9.5

CRAN release: 2025-02-07

• New pkgdown website for the package
  • This package now has a documentation site at https://statisticsnorway.github.io/ssb-gausssuppression/.
• Matrix are moved from Depends to Imports
  • To follow best practices for R packages
• Utilizing updates in the SSBtools package (version 1.7.0).
  • The new function tables_by_formulas(), which is now reexported, is demonstrated in a SuppressSmallCounts() example and a SuppressDominantCells() example.
    
  • The new function Extend0fromModelMatrixInput() is now used in data pre-processing. As a result, hierarchical_extend0 is now a possible parameter, as illustrated in a SuppressSmallCounts() example.
• Improvements to GaussSuppressDec() and SuppressionFromDecimals()
  • GaussSuppressDec() now accepts wrappers as input, such as SuppressSmallCounts() and SuppressDominantCells().
  • Added new parameter use_freqVar to allow decimal numbers to be generated solely from 0s, improving stability.
  • All output variables from the underlying function are now included in the default output of GaussSuppressDec().
  • FormulaSelection() now works correctly with output from GaussSuppressDec().
  • SuppressionFromDecimals() has been updated accordingly. In particular, automation is now implemented to detect whether decimal numbers are generated from 0s or from frequencies.

GaussSuppression 0.9.2

CRAN release: 2024-12-09

• Added a check to ensure that at least one of dimVar, hierarchies, or formula is specified.
  • This is a breaking change that may affect previous code.
  • Previously, if all were unspecified, dimVar was automatically generated from the remaining columns.
  • While this behavior was correctly implemented, it often stemmed from user input errors and could lead to unexpected behavior or crashes.
  • This change now requires explicit input, making the function more robust and reducing the risk of user errors.
• SuppressDominantCells() and the underlying function MagnitudeRule() have been improved:
  • contributorVar (charVar) can now be combined with sWeightVar.
  • Improved handling of protectZeros. See this parameter’s documentation in ?MagnitudeRule.
  • New parameter removeCodesFraction allows adjustment of the effect of the removeCodes parameter.
  • New parameter apply_abs_directly determines how negative values are treated in the rules:
    • When apply_abs_directly = FALSE (default), absolute values are taken after summing contributions, as performed by max_contribution() in the SSBtools package.
    • When 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.
  • Enhanced output when allDominance = TRUE:
    • Renaming: The variable previously called primary.2:80 ((2,80) dominance)) is now dominant2.
    • IDs associated with the largest contributions are now included.
    • The number of contributors is also included.
    • Additional outputs are available. See the documentation of the allDominance parameter.
  • The new functionality has been enabled by replacing MaxContribution() with the improved max_contribution() from SSBtools.
• Improved support for tibble and data.table input (parameter data).
  • Input is now explicitly coerced to a data frame using as.data.frame() where necessary to ensure consistent behavior.
  • When 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.
  • Applies to GaussSuppressionFromData() and its wrappers.
• The SSBtools functions FormulaSelection() and its identical wrapper formula_selection() are now re-exported.
  • These functions are useful for extracting smaller datasets from the output.
    
  • With this change, using library(SSBtools) is no longer necessary to access them.
    
• Note new hierarchy possibilities due to the new version of the SSBtools package (version 1.6.0).

  • Output from functions like 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)) 

  • New possibilities for working with both formulas and hierarchies are now available through the map_hierarchies_to_data() function.

  • Improved functionality for combining formulas with the Formula2ModelMatrix() parameter avoidHierarchical = TRUE, thanks to the new total_collapse() function which can be applied to output.

GaussSuppression 0.9.0

CRAN release: 2024-09-24

• The Gaussian elimination secondary suppression algorithm has now been documented in a “Privacy in Statistical Databases 2024” paper.
  • The package description has been updated with this reference (Langsrud, 2024).
• Due to updates in the SSBtools package (version 1.5.4), it is now meaningful to include NA’s in the grouping variables.
  • Note the parameter NAomit to SSBtools::Formula2ModelMatrix():
    • When TRUE, NAs in the grouping variables are omitted in output and not included as a separate category.
    • This parameter can be input to GaussSuppressionFromData() and its wrappers.
  • aggregateNA is new parameter to GaussSuppressionFromData():
    • Whether to include NAs in the grouping variables while preAggregate/extraAggregate.
    • Needs to be TRUE (default) to utilize the above NAomit parameter.
• Due to updates in the SSBtools package (version 1.5.4), where data.table is now listed under Suggests, some functionality can be speeded up.
  • Set the new parameter aggregatePackage to "data.table" to utilize this possibility.
    • aggregatePackage is parameter to GaussSuppressionFromData() and its wrappers.
    • Also note the related new parameters aggregateBaseOrder and rowGroupsPackage.

GaussSuppression 0.8.8

CRAN release: 2024-06-28

• A bug related to the remove0 parameter is now fixed
  • There was a bug related to the remove0 parameter in SuppressFewContributors/NContributorsRule introduced in version 0.8.0. When a single numVar was used as input, the remove0 functionality failed.

GaussSuppression 0.8.5

CRAN release: 2024-05-22

• SuppressDominantCells() is now considered a common function for both the nk-dominance rule and the p-percent rule.
  • The pPercent parameter is now exposed in the SuppressDominantCells() documentation.
• The n parameter in SuppressDominantCells() now defaults to 1:length(k).
  • To simplify common use.
• A problem in experimental interval suppression is now fixed.
  • It was a bug occurring in cases where a response value of zero was secondary suppressed.
• Improvements due to updates in the SSBtools package (version 1.5.2).
  • Fix for a rare problem in GaussSuppression(),
    • Could happen with parallel eliminations combined with integer overflow. Then warning message: longer object length is not a multiple of shorter object length
  • Minor change to the singleton method "anySum" in GaussSuppression() to align with best theory.
    • In practice, this rarely makes a difference.
    • The previous behavior can be ensured by setting singletonMethod to either "anySumOld" or "anySumNOTprimaryOld".

GaussSuppression 0.8.3

CRAN release: 2024-03-22

• Experimental functionality to meet interval width requirements has been incorporated
  • If at least one of the two parameters below is specified, in addition to the lpPackage parameter, further suppression will be performed to satisfy the interval width requirements.
    • rangePercent: Required interval width expressed as a percentage
    • rangeMin: Minimum required width of the interval

GaussSuppression 0.8.0

CRAN release: 2024-02-02

• Improved singleton methods for magnitude tables
  • A new default setting, singletonMethod = "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 “….”.
    • To prevent this doubling, set singletonMethod = "numttHtT".
    • The behavior of version 0.7.0 can be restored by setting singletonMethod = "numttH".
    • A simpler and faster method is achievable with singletonMethod = "numttT".
    • As in previous versions, singleton handling can be disabled by setting singletonMethod = "none".
  • Additional information can be found by ?SSBtools::NumSingleton.
  • Some explanation is provided at the bottom of the magnitude vignette.
  • This will later be documented in a more comprehensive manner (paper).
• Improved functionality of the SuppressDominantCells() and SuppressFewContributors() wrappers.
  • Improved support for handling multiple numerical variables, introducing new parameters: dominanceVar and candidatesVar.
  • The removeCodes parameter is now also available in the DominanceRule() and SuppressDominantCells() functions.
  • Support for multiple contributorVar (charVar) in the SuppressFewContributors() and NContributorsRule() functions.
  • Now, 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.
  • The update described below enables the specification of the pPercent parameter directly through SuppressDominantCells().
• The p% rule for magnitude tables has been implemented through the introduction of a new primary suppression function, PPercentRule().
  • Technically, PPercentRule() and DominanceRule() now serve as wrappers for the newly introduced. general function MagnitudeRule().
• AdditionalSuppression() generalized to take a wrappers as input.
• New special functions for the avoidance of suppression
  • PrimaryRemoveWg(), CandidatesNumWg() and ForcedWg()
• Experimental functionality for interval calculations has been included
  • Intervals can now be calculated using the new function ComputeIntervals().
  • When the 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.

GaussSuppression 0.7.0

CRAN release: 2023-06-07

• More vignettes are included.
• Better singleton handling for magnitude tables when using SuppressDominantCells() and SuppressFewContributors().
  • Due to improvements in the SSBtools package (version 1.4.6).
  • Due to new default extraAggregate = TRUE in the specs, dominanceSpec and fewContributorsSpec.
• More default values are explicitly included in the in specs so that they are easier seen.
  • See PackageSpecs().

GaussSuppression 0.6.0

CRAN release: 2023-03-31

• A vignette entitled “Defining Tables for GaussSuppression” is now included.
• Now, easy-to-use wrapper functions are included.
  • SuppressSmallCounts(), SuppressDominantCells(), and SuppressFewContributors(), along with SuppressKDisclosure() (which was available in the previous version).
• Built-in specs that contribute to a simpler interface have been adopted.
  • See PackageSpecs().
• Sampling weights are now possible in the dominance rule.
  • See DominanceRule().
• More advanced singleton handling that makes use of new functionality in the SSBtools package (version 1.4.4).
  • See SSBtools::GaussSuppression().
  • See SingletonUniqueContributor().
• Now forced and usafe are possible output columns.
  • Where unsafe means unsafe primary suppressions due to forced cells. That, is the unsafe primarily suppressed values can be re-calculated from the values of the cells forced to be not suppressed.
  • See parameters forcedInOutput and unsafeInOutput to GaussSuppressionFromData().

GaussSuppression 0.5.0

CRAN release: 2022-08-30

• Now the original variable names, as specified by freqVar and weightVar, are kept in the output.
  • In previous versions these names were standardized to "freq" and "weight".
  • Code relying on previous behavior with other 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).
• Adaption needed after Matrix ver. 1.4-2 (not a user-visible change)

GaussSuppression 0.4.0

CRAN release: 2022-06-28

• Last version before any news