simple_dis: Simple generation of new variables

In statistikat/simPop: Simulation of Complex Synthetic Data Information

Simple generation of new variables

Description

Fast simulation of new variables based on univariate distributions

Usage

univariate.dis(puf, data, additional, weights, value = "data", fNA = NA)

conditional.dis(
  puf,
  data,
  additional,
  conditional,
  weights,
  value = "data",
  fNA = NA
)

Arguments

puf	data for which one additional column specified by function argument ‘additional’ is simulated
data	donor data
additional	name of variable to be simulated
weights	sampling weights from data
value	if “data” then the puf including the additional variable is returned, otherwise only the simulated vector.
fNA	only used with missing values if another code as NA should be used
conditional	conditioning variable

Details

Function uni.distribution: random draws from the weighted univariate distribution of the original data

Function conditional.dis: random draws from the weighted conditional distribution (conditioned on a factor variable)

This are simple functions to produce structural variables, variables that should have the same categories as given ones. For more advanced methods see simCategorical()

Author(s)

Lydia Spies, Matthias Templ

See Also

simCategorical

Examples

## we don't have original data, so let's use eusilc
data(eusilc13puf)
data(eusilcS)
v1 <- univariate.dis(eusilcS, eusilc13puf, additional = "db040",
weights = "rb050", value = "vector")
table(v1)
table(eusilc13puf$db040)
## we don't have original data, so let's use eusilc
##data(eusilc13puf)
##data(eusilcS)
##v1 <- conditional.dis(eusilcS, eusilc13puf, additional = "pb190",
##  conditional = "db040", weights = "rb050")
##table(v1) / sum(table(v1))
##table(eusilc13puf$pb190) / sum(table(eusilc13puf$pb190))

statistikat/simPop documentation built on March 24, 2024, 5:05 a.m.