Description Usage Arguments Details Value Reserved characters Note References See Also Examples
Impute a data frame imprecisely
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recipient 
a data.frame acting as recipient; see details. 
donor 
a data.frame acting as donor; see details. 
method 
1character string of the desired imputation method.
The following values are possible, see details for an explanantion:

matchvars 
a character vector containing the variable names
to be used as matching variables. If 
vardomains 
a named list containing the possible values of
all variable in 
x 
object of class 'impimp' 
... 
further arguments passed down to

z 
object to test for class 
As in the context of statistical matching the data.frames
recipient
and donor
are assumed to contain an
overlapping set of variables.
The missing values in recipient
are subsituted with
observed values in donor
for approaches based on donation
classes and otherwise with the set of all possible values for
the variable in question.
For method = "domain"
a missing value of a variable in
recipient
is imputed by the set of all possible values
of that variable.
The other methods are based on donation classes which are formed
based on the matching variables whose names are provided by
matchvars
. They need to be present in both recipient
and donor
:
For method = "variable_wise"
a missing value of a variable
in recipient
is imputed by the set of all observed values
of that variable in donor
.
For method = "case_wise"
the variables only present in
donor
are represented as tuples. A missing tuple in
recipient
is then imputed by the set of all observed
tuples in donor
.
The data.frame resulting in an imprecise imputation
of donor
into recipient
.
It is also of class "impimp"
and stores the imputation
method in its attribute "impmethod"
, the names of the
variables of the resulting object containing imputed values
in the attribute "imputedvarnames"
, as well as the
list of (guessed) levels of each underlying variable in
"varlevels"
.
The variable names and observations in recipient
and
donor
must not contain characters that are reserved for
internal purpose.
The actual characters that are internally used are stored in the
options options("impimp.obssep")
and
options("impimp.varssep")
. The former is used to separate
the values of a setvalued observation, while the other is used
for a concise tupel representation.
This method does not require that all variables in recipient
and donor
are factor
variables, however,
the imputation methods apply coercion to factor, so purely
numerical variables will be treated as factors eventually.
It does assume (and test for it) that there are no missing
values present in the matching variables.
Endres, E., Fink, P. and Augustin, T. (2018), Imprecise Imputation: A Nonparametric Micro Approach Reflecting the Natural Uncertainty of Statistical Matching with Categorical Data, Department of Statistics (LMU Munich): Technical Reports, No. 214. URL https://epub.ub.unimuenchen.de/42423/.
for the estimation of probabilities impest
and impestcond
; rbindimpimp
for
joining two impimp
objects
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