
## SSBtools 1.8.8
* Bugfix in `model_aggregate()` for special cases where `fun_vars` or `sum_vars` overlap 
  with other variable names (`preagg_var` and the table's dimension variables).
  - For `fun_vars`, this is resolved by changing how `dummy_aggregate()` handles duplicated 
    variable names: the last occurrence is now used.
  - For `sum_vars`, duplicated variable names in an internal data frame are
    similarly resolved by keeping the last occurrence.
* Changed the `convert_integer()` example to avoid using a function that will be unexported in a future release of 
  [bit64](https://cran.r-project.org/package=bit64). 
  - Thanks to Michael Chirico for reporting the issue ([#142](https://github.com/statisticsnorway/ssb-ssbtools/issues/142)) 
  and providing the fix ([#143](https://github.com/statisticsnorway/ssb-ssbtools/pull/143)).

## SSBtools 1.8.7
* Fix in `table_all_integers()`
  - Avoid base R `factor()` bug causing every 100,000th table count to be incorrectly set to 0.
  - See [GaussSuppression issue #155](https://github.com/statisticsnorway/ssb-gausssuppression/issues/155)

## SSBtools 1.8.6
* Added support for named total vectors in `ModelMatrix()` and related functions.
  - `FormulaSums()`/`Formula2ModelMatrix()` can now accept multiple total codes
    via named total vectors.
  - See also the underlying functions `FindDimLists()` and `AutoHierarchies()`,
    which now also support named total vectors.
  - `tables_by_formulas()` has been updated so that named total vectors are handled
    flexibly in connection with both `substitute_vars` and `collapse_vars`.
* New function `convert_integer64()`.
  - Helper for converting `integer64` data (from 
  [bit64](https://cran.r-project.org/package=bit64) 
  or 
  [arrow](https://cran.r-project.org/package=arrow) 
  imports) 
    to base R `integer`, `numeric`, or `character`.
* `max_contribution()` now accepts integer vectors for `y`. 
  - Previously, integer input caused an error due to dgTMatrix in the Matrix package requiring a numeric (double) `x` slot.


## SSBtools 1.8.4
* New functions `diff_groups()` and `data_diff_groups()`:
  - Identify and describe relationships between paired codes, and add results
    back to data frames.
* New example datasets `code_pairs`, `barcelona2025`, `paris2025_freq`, and `paris2025_micro`.


## 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](https://statisticsnorway.github.io/ssb-ssbtools/) and the 
  [GitHub repository](https://github.com/statisticsnorway/ssb-ssbtools).

## SSBtools 1.7.0 
* **New pkgdown website for the package**  
  - This package now has a documentation site at [https://statisticsnorway.github.io/ssb-ssbtools/](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](https://cran.r-project.org/package=klassR) 
    or `hier_create()` in the 
    [sdcHierarchies package](https://cran.r-project.org/package=sdcHierarchies) 
    can now be used directly as input. 
  - Example of usage:
    ```r
    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](https://cran.r-project.org/package=GaussSuppression).
* 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)](https://doi.org/10.1007/978-3-031-69651-0_6). 
* 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)](https://doi.org/10.32614/RJ-2023-088).
* 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
