mafast {sdcMicro}

Fast and Simple Microaggregation

Description

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

Usage

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)

Value

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.

Author(s)

Alexander Kowarik

See Also

microaggregation

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"
  )
})