GaussSuppressionFromData
is run and decimal numbers are added to output by
a modified (for sparse matrix efficiency) version of SuppressDec
.
GaussSuppressDec(
data,
...,
output = NULL,
digits = 9,
nRep = NULL,
rmse = pi/3,
sparseLimit = 500,
rndSeed = 123,
runIpf = FALSE,
eps = 0.01,
iter = 100,
mismatchWarning = TRUE,
whenDuplicatedInner = NULL,
whenMixedDuplicatedInner = warning
)
A data frame where inner cells and cells to be published are combined or output according to parameter output
.
Input daata as a data frame
Further parameters to GaussSuppressionFromData
NULL (default), "publish"
, "inner"
, "publish_inner"
, or "publish_inner_x"
(x also).
Parameter to RoundWhole
. Values close to whole numbers will be rounded.
NULL or an integer. When >1, several decimal numbers will be generated.
Desired root mean square error of decimal numbers. Variability around the expected, according to the linear model, inner frequencies. The expected frequencies are calculated from the non-suppressed publishable frequencies.
Limit for the number of rows of a reduced x-matrix within the algorithm. When exceeded, a new sparse algorithm is used.
If non-NULL, a random generator seed to be used locally within the function without affecting the random value stream in R.
When TRUE, additional frequencies are generated by iterative proportional fitting using Mipf
.
Parameter to Mipf
.
Parameter to Mipf
.
Whether to produce the warning "Mismatch between whole numbers and suppression
", when relevant.
When nRep>1
, all replicates must satisfy the whole number requirement for non-suppressed cells.
When mismatchWarning
is integer (>0
), this will be used as parameter digits
to RoundWhole
when doing mismatch checking (can be quite low when nRep>1
).
Function to be called when default output and when cells marked as inner correspond to several input cells (aggregated) since they correspond to published cells.
Function to be called in the case above when some inner cells correspond to published cells (aggregated) and some not (not aggregated).
Øyvind Langrsud
z1 <- SSBtoolsData("z1")
GaussSuppressDec(z1, 1:2, 3)
GaussSuppressDec(z1, freqVar = "ant", formula = ~ region + hovedint, maxN = 10)
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