mafast function

Fast and Simple Microaggregation

Function to perform a fast and simple (primitive) method of microaggregation. (for large datasets) methods

mafast(obj, variables = NULL, by = NULL, aggr = 3, measure = mean)

Arguments

• obj: either a sdcMicroObj-class-object or a data.frame
• variables: variables to microaggregate. If obj is of class sdcMicroObj the numerical key variables are chosen per default.
• by: grouping variable for microaggregation. If obj is of class sdcMicroObj the strata variables are chosen per default.
• aggr: aggregation level (default=3)
• measure: aggregation statistic, mean, median, trim, onestep (default = mean)

Returns

If obj was of class sdcMicroObj-class the corresponding slots are filled, like manipNumVars, risk and utility. If obj was of class data.frame or matrix an object of the same class is returned.

Examples

data(Tarragona)
m1 <- mafast(Tarragona, variables=c("GROSS.PROFIT","OPERATING.PROFIT","SALES"),aggr=3)
data(testdata)
m2 <- mafast(testdata,variables=c("expend","income","savings"),aggr=50,by="sex")
summary(m2)

## for objects of class sdcMicro:
data(testdata2)
sdc <- createSdcObj(testdata2,
  keyVars=c('urbrur','roof','walls','water','electcon','relat','sex'),
  numVars=c('expend','income','savings'), w='sampling_weight')
sdc <- dRisk(sdc)
sdc@risk$numeric
sdc1 <- mafast(sdc,aggr=4)
sdc1@risk$numeric

sdc2 <- mafast(sdc,aggr=10)
sdc2@risk$numeric

### Performance tests
x <- testdata
for(i in 1:20){
  x <- rbind(x,testdata)
}
system.time({
  xx <- mafast(
    obj = x,
    variables = c("expend", "income", "savings"),
    aggr = 50,
    by = "sex"
  )
})

See Also

microaggregation

Author(s)

Alexander Kowarik