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SSBtools 1.8.2

• New functions zero_col() and single_col():
  • Previously internal only, now exported for use in other packages.
• New helper function get_colnames():
  • Returns column names based on either indices or names, working consistently across data.frame, tibble, and data.table.

SSBtools 1.8.1

• GaussSuppression() updates:
  • Now handles negative values in the model matrix.
    
  • Added new parameter auto_subSumAny to optionally disable the automatic switch of the singleton method.
    
  • These changes prepare GaussSuppression() for use in a new algorithm for linked tables.
• DummyDuplicated() improvements:
  • Now supports empty matrix input (0 columns and/or 0 rows).
    
  • The documentation remark “(dummy matrix not required)” is now more accurate.
    • Previously, columns with a column sum of 0 were treated as if they contained only zeros.
• New function any_duplicated_rows():
  • Fast alternative to base::anyDuplicated(), implemented similarly to RowGroups().

SSBtools 1.8.0

• The GaussSuppression() function is updated with a new parameter: cell_grouping.
  • This allows certain cells to be suppressed or non-suppressed together.
    
  • The change enables a consistent linked-table algorithm, achieved by using an x input structured as a block-diagonal matrix.
    
  • See also the related new parameters: table_id and auto_anySumNOTprimary.
• New function formula_term_labels().
  • Part of the utility functions listed under ?formula_utils.
    
  • Extracts term labels from the right-hand side of a given R formula.
• Functionality to extract term labels from a data frame.
  • New function output_term_labels().
    
  • New parameter term_labels in tables_by_formulas(), used to include term labels in the output.

SSBtools 1.7.5

• The title and description in the DESCRIPTION file have been updated
  to avoid giving the impression that the package is strictly internal to Statistics Norway.
• Matrix are moved from Depends to Imports
  • To follow best practices for R packages.
• Removed dependency on stringr
  • Ensures that SSBtools has no dependencies beyond standard R packages.
  • Replaced stringr::str_split() with base R alternatives in WildcardGlobbingVector() and HierarchicalWildcardGlobbing().
• Fixed usage of the invert parameter in WildcardGlobbingVector() and HierarchicalWildcardGlobbing().
  • Previously, the default value was always used.
  • This change was made now because this code was reviewed as part of removing the stringr dependency.
• A small improvement to a singleton method in GaussSuppression(), along with a minor fix.
  • See the note under ?NumSingleton for details on the improvement to elimination (4th character).
    
  • A previous attempt for a similar improvement was not implemented correctly,
    which in rare cases could lead to unnecessary secondary cells. This has now been fixed.
• Improved robustness of RbindAll().
  • RbindAll() now correctly handles data frames with 0 rows instead of producing an error.
    
  • RbindAll() now also accepts NULL as input.
    
• A hexagon sticker logo is now visible on the pkgdown website and the GitHub repository.

SSBtools 1.7.0

• New pkgdown website for the package
  • This package now has a documentation site at https://statisticsnorway.github.io/ssb-ssbtools/.
• New function: tables_by_formulas()
  • This function acts as an overlay for functions that produce tabular statistics through an interface utilizing the ModelMatrix() function and its formula parameter.
  • Each table (individual statistic) is defined by a formula. The output is a single data.frame that contains the results for all tables.
• Improvements to model_aggregate()
  • Now, avoid_hierarchical, input_in_output, and total are direct parameters to model_aggregate().
    • Previously, the corresponding ModelMatrix() parameters (avoidHierarchical, inputInOutput, and total) had to be set via the mm_args parameter. Old code remains functional.
      
  • Improved support for tibble and data.table input (parameter data).
    • Input is now explicitly coerced to a data frame using as.data.frame() to ensure consistent behavior.
      
  • The pre-aggregation functionality in model_aggregate() can now be speeded up.
    • Set the new parameter aggregate_pkg = "data.table" to utilize this possibility. Also note the related new parameter aggregate_base_order.
      
  • Added a new parameter, aggregate_na, to control handling of missing values in grouping variables.
    • This is linked to the NAomit parameter to Formula2ModelMatrix(), which makes it meaningful to include NAs in the grouping variables.
      
    • When aggregate_na = TRUE, NAs in grouping variables are retained during pre-aggregation.
      
• Improved GaussSuppression() – now removes duplicate rows
  • See the updated documentation for the removeDuplicated parameter.
    
  • Previously, only duplicate columns were removed.
    
  • This update improves speed, especially when the function is called through an interface based on ModelMatrix() that uses the hierarchies parameter together with inputInOutput = FALSE.
    
  • Also note the related new parameter, printXdim, which can be used to print information about dimensional changes to the console.
    
• Improvements to map_hierarchies_to_data()
  • Duplicate variable names are now handled. See the new parameter when_overwritten.
    
  • A comment attribute is added to the output data frame, containing the names of the variables that were added. See the new parameter add_comment.
    
• Improvements to hierarchies_as_vars()
  • See the new parameters drop_codes and include_codes.
    
• Intercept problem in combine_formulas() is fixed
  • When combining formulas with and without intercept using the "+" operator,
    it is now ensured that the resulting formula includes an intercept.
    
• Additional new functions
  • filter_by_variable() and names_by_variable() are functions to
    filter a list of items or retrieve names based on a variable.
    
  • Extend0fromModelMatrixInput(), marked as internal, is a specialized version of Extend0()
    designed specifically to work with input to ModelMatrix().

SSBtools 1.6.0

• AutoHierarchies() has been updated to recognize common from-to names, and the sign variable is now optional.

  • See the new parameter autoNames for details on common from-to names.

  • Also note the new parameter autoLevel, with a default value (TRUE) that ensures the function behaves as it always has.

  • NAs in the ‘to’ variable are now allowed to support common hierarchies, and rows where ‘to’ == ‘from’ are also allowed. Such rows are removed before processing the hierarchy, with a warning when relevant (Codes removed due to ‘to’ == ‘from’ or ‘to’ == NA).

  • 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])
    AutoHierarchies(list(tree = a, letter = b))

• New hierarchy functionality with hierarchies coded as variables (minimal datasets):
  • New function hierarchies_as_vars():
    • Hierarchies coded as variables.
  • New function vars_to_hierarchies():
    • Transform hierarchies coded as variables to “to-from” format.
    • A kind of reverse operation of hierarchies_as_vars().
  • New function map_hierarchies_to_data():
    • Add variables to dataset based on hierarchies.
    • Uses hierarchies_as_vars() to transform hierarchies, followed by mapping to the dataset.
• New function max_contribution() with wrapper n_contributors().
  • Find major contributions to aggregates and count contributors.
  • Improved versions of MaxContribution() and Ncontributors() developed in the GaussSuppression package.
• New function table_all_integers().
  • Table all integers from 1 to n
• New function total_collapse().
  • Collapse variables to single representation.
• New function substitute_formula_vars().
  • Part of the utility functions listed under ?formula_utils.
  • An improved version of formula_include_hierarchies(), which has been renamed for clarity and corrected to produce the intended output.
• Allow “empty terms” in FormulaSums() when viaSparseMatrix = TRUE.
  • “Empty terms” refer to cases where no columns exist in the model matrix due to NAomit.
  • The old method (viaSparseMatrix = FALSE) already handled this correctly.
• Minor improvement to Extent0().
  • Now allows 0 input rows when hierarchical = FALSE.
• Minor improvement to FormulaSelection() and its identical wrapper formula_selection().
  • Now supports 0-length selections.

SSBtools 1.5.5

• The function FormulaSelection() and thereby the identical wrapper formula_selection() have been generalized.
  • New parameter named logical: When TRUE, the logical selection vector is returned.
  • FormulaSelection() is now a generic function, allowing methods for other input objects to be added.

SSBtools 1.5.4

• The GaussSuppression() function and related functionality have now been documented in a “Privacy in Statistical Databases 2024” paper.
  • The package description and function documentations have been updated with this reference (Langsrud, 2024).
• Now the data.table package is listed under Suggests and can be utilized in two functions. See below.
• New function, aggregate_by_pkg()
  • This function aggregates data by specified grouping variables, using either base R or data.table.
  • Note the parameter include_na: A logical value indicating whether NA values in the grouping variables should be included in the aggregation. Default is FALSE.
  • Will be used in packages depending on SSBtools.
• NAomit is new parameter to RowGroups() and Formula2ModelMatrix()/FormulaSums().
  • This is about NAs in the grouping variables.
  • The parameter can be used as input to ModelMatrix().
• pkg is new parameter to RowGroups()
  • Must be either "base" (default) or "data.table" (for improved speed).
• Improved speed of Formula2ModelMatrix()/FormulaSums().
  • Thus, improved speed of ModelMatrix().
  • Now, the model matrix is constructed by a single call to Matrix::sparseMatrix() instead of building the transposed matrix with rbind() based on numerous Matrix::fac2sparse() calls.
  • Further speed improvement can be achieved by setting the new parameter, rowGroupsPackage, to data.table.
• An efficiency bug in ModelMatrix() is fixed.
  • With viaOrdinary = TRUE, model.matrix() or sparse.model.matrix() was called twice.
• combine_formulas() is improved
  • A long string problem solved, when long formulas.
• Some technical changes in documentation to comply with standards.

SSBtools 1.5.2

• The ModelMatrix() function and related functionality for hierarchical computations have now been documented in a paper in The R Journal.
  • The package description has been updated with this reference (Langsrud, 2023).
• Now, remove_empty is an explicit parameter to model_aggregate().
  • Previously, this had to be done via the mm_args parameter. Old code works as before.
• Some tools for formula manipulation are included.
  • See ?formula_utils
• Minor change in Extend0() to allow even more advanced possibilities by varGroups-attribute.
• 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".
• Fixed a zero-weight issue in quantile_weighted().
  • Now, quantile_weighted(x=c(0,2,0), weights = c(1,1,0)) correctly outputs the 50% value as 1.
    
• A function for checking function inputs has been included and can be used as either CheckInput() or check_input().
  • The function was originally created in 2016 and has been included in internal packages at Statistics Norway (SSB). Due to its widespread use, it was beneficial to include it in this CRAN package.

SSBtools 1.5.0

• Last version before any news

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