Synthesis by unordered polytomous regression
syn.polyreg.RdGenerates a synthetic categorical variable using unordered polytomous regression (without or with bootstrap).
Arguments
- y
an original data vector of length
n.- x
a matrix (
nxp) of original covariates.- xp
a matrix (
kxp) of synthesised covariates.- proper
for proper synthesis (
proper = TRUE) a multinomial model is fitted to a bootstrapped sample of the original data.- maxit
the maximum number of iterations for
nnet.- trace
switch for tracing optimization for
nnet.- MaxNWts
the maximum allowable number of weights for
nnet.- ...
additional parameters passed to
nnet.
Details
Generates synthetic categorical variables by the polytomous regression model. The method consists of the following steps:
Fit categorical response as a multinomial model.
Compute predicted categories.
Add appropriate noise to predictions.
The algorithm of syn.polyreg uses the function
multinom from the nnet package. Any numerical
variables are scaled to cover the range (0,1) before fitting. Warnings
are printed if the algorithm fails to converge in maxit iterations
and also if the synthesised data has only one category. The latter may occur
if the variable being synthesised is sparse so that the algorithm fails to
iterate.
In order to avoid bias due to perfect prediction, the data are augmented by the method of White, Daniel and Royston (2010).
NOTE that when the function is called by setting elements of method in syn()
to "polyreg", the parameters maxit, trace and MaxNWts
can be supplied to syn() as e.g. polyreg.maxit.
Value
A list with two components:
- res
a vector of length
kwith synthetic values ofy.- fit
a summary of the model fitted to the observed data and used to produce synthetic values.