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.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:
<- get_klass(classification = "24")
a <- hier_create(root = "Total", nodes = LETTERS[1:5])
b <- data.frame(tree = sample(a$code[nchar(a$code) > 1], 200, replace = TRUE),
mydata letter = LETTERS[1:5])
PLSroundingPublish(mydata, roundBase = 5, 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.
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