dimVar
, hierarchies
, or formula
is specified.
dimVar
was automatically generated from the remaining columns.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.PLSrounding()
and its wrappers.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])
PLSroundingPublish(mydata, roundBase = 5, 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.FormulaSelection()
now works with the output from PLSrounding()
.
extend0
is new parameter to PLSrounding()
, enabling data to be automatically extended by zero frequency rows.
zeroCandidates = TRUE
.PLSroundingFits()
has been renamed from extend0
to extend0Fits
. Code that used the old parameter will now behave differently.extend0
and extend0Fits
can now be specified in more advanced ways beyond just TRUE/FALSE.step
parameter, which can be passed to PLSrounding()
and is documented in the underlying function RoundViaDummy()
:
step
has been fixed.step
parameter can now be specified as a vector for greater control.step
parameter can significantly impact performance on large datasets. For example, using step = list(100)
may be a useful approach.NAomit
to SSBtools::Formula2ModelMatrix()
:
TRUE
, NAs in the grouping variables are omitted in output and not included as a separate category.PLSrounding()
and its wrappers.aggregateNA
is new parameter to PLSrounding()
:
TRUE
(default) to utilize the above NAomit
parameter.aggregatePackage
to "data.table"
to utilize this possibility.
aggregatePackage
is parameter to PLSrounding()
and its wrappers.aggregateBaseOrder
.R
versions where the isFALSE
function is not defined.identifyNew
parameter when the maxRound
parameter is used.
identifyNew
parameter:
When TRUE
, new cells may be identified after initial rounding to ensure all rounded publishable
cells equal to or less than maxRound
to be roundBase
multiples. Use NA
for the a less conservative
behavior (old behavior). Then it is ensured that no nonzero rounded publishable cells are smaller
than roundBase
. When maxRound
is default, there is no difference between TRUE
and NA
.PLSroundingLoop
: PLSrounding on portions of data at a time.
preDifference
)zeroCandidates
, forceInner
, preRounded
and plsWeights
can now be specified as functions.
PLSroundingLoop
.allSmall
.
<= maxRound
) are rounded. A simplified alternative to specifying forceInner
.PLSroundingFits
, for post-processing to expected frequencies
plsWeights
is new parameter to RoundViaDummy
(and PLSrounding
)
freqVar
in input.preAggregate
: When TRUE
, the data will be aggregated beforehand within the function by the dimensional variables.avoidHierarchical
to Formula2ModelMatrix
in the SSBtools package.rndSeed
, a new parameter to RoundViaDummy
(and PLSrounding
).rndSeed = 123
. This means that repeated runs with equal input will result in equal output.rndSeed
to NULL
."inner"
or "publish"
.
output
, a new parameter to PLSrounding
.PLSroundingInner
and PLSroundingPublish
.dimVar
is new parameter to RoundViaDummy
and PLSrounding
preRounded
is new parameter to RoundViaDummy
(and PLSrounding
)
HierarchiesAndFormula2ModelMatrix
in the SSBtools packageleverageCheck
and easyCheck
are new parameters to RoundViaDummy
Reduce0exact
in the SSBtools package is utilisedprintInc
is new parameter to PLSrounding
and RoundViaDummy
removeEmpty=TRUE
to omit empty combinations
Hierarchies2ModelMatrix
and HierarchiesAndFormula2ModelMatrix
in the SSBtools packageinputInOutput
is also mentioned in the RoundViaDummy documentation