Description Usage Arguments Details Value Note Author(s) See Also Examples
Simulate categorical variables of population data taking relationships
between household members into account. The household structure of the
population data needs to be simulated beforehand using
simStructure
.
1 2 3 4 
simPopObj 
a 
relation 
a character string specifying the columns of 
head 
a character string specifying the category of the variable given
by 
direct 
a character string specifying categories of the variable given
by 
additional 
a character vector specifying additional categorical
variables of 
limit 
this can be used to account for structural zeros. If only one additional variable is requested, a named list of lists should be supplied. The names of the list components specify the predictor variables for which to limit the possible outcomes of the response. For each predictor, a list containing the possible outcomes of the response for each category of the predictor can be supplied. The probabilities of other outcomes conditional on combinations that contain the specified categories of the supplied predictors are set to 0. If more than one additional variable is requested, such a list of lists can be supplied for each variable as a component of yet another list, with the component names specifying the respective variables. 
censor 
this can be used to account for structural zeros. If only one
additional variable is requested, a named list of lists or

maxit, MaxNWts 
control parameters to be passed to

eps 
a small positive numeric value, or 
nr_cpus 
if specified, an integer number defining the number of cpus that should be used for parallel processing. 
seed 
optional; an integer value to be used as the seed of the random number generator, or an integer vector containing the state of the random number generator to be restored. 
The values of a new variable are simulated in three steps, where the second
step is optional. First, the values of the household heads are simulated
with multinomial loglinear models. Second, individuals directly related to
the corresponding household head (as specified by the argument
direct
) inherit the value of the latter. Third, the values of the
remaining individuals are simulated with multinomial loglinear models in
which the value of the respective household head is used as an additional
predictor.
The number of cpus are selected automatically in the following manner. The number of cpus is equal the number of strata. However, if the number of cpus is less than the number of strata, the number of cpus  1 is used by default. This should be the best strategy, but the user can also overwrite this decision.
An object of class simPopObj
containing survey
data as well as the simulated population data including the categorical
variables specified by additional
.
The basic household structure needs to be simulated beforehand with
the function simStructure
.
Andreas Alfons and Bernhard Meindl
simStructure
, simCategorical
,
simContinuous
, simComponents
1 2 3 4 5 6 7 8 9 10 11  data(ghanaS) # load sample data
samp < specifyInput(data=ghanaS, hhid="hhid", strata="region", weight="weight")
ghanaP < simStructure(data=samp, method="direct", basicHHvars=c("age", "sex", "relate"))
class(ghanaP)
## Not run:
## long computation time ...
ghanaP < simRelation(simPopObj=ghanaP, relation="relate", head="head")
str(ghanaP)
## End(Not run)

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