dataGen {sdcMicro} | R Documentation |
Fast generation of synthetic data
Description
Fast generation of (primitive) synthetic multivariate normal data.
Usage
dataGen(obj, ...)
Arguments
obj |
an |
... |
see possible arguments below
|
Details
Uses the cholesky decomposition to generate synthetic data with approx. the same means and covariances. For details see at the reference.
Value
the generated synthetic data.
Note
With this method only multivariate normal distributed data with approxiomately the same covariance as the original data can be generated without reflecting the distribution of real complex data, which are, in general, not follows a multivariate normal distribution.
Author(s)
Matthias Templ
References
Mateo-Sanz, Martinez-Balleste, Domingo-Ferrer. Fast Generation of Accurate Synthetic Microdata. International Workshop on Privacy in Statistical Databases PSD 2004: Privacy in Statistical Databases, pp 298-306.
See Also
Examples
data(mtcars)
cov(mtcars[,4:6])
cov(dataGen(mtcars[,4:6]))
pairs(mtcars[,4:6])
pairs(dataGen(mtcars[,4:6]))
## 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 <- dataGen(sdc)