I am trying to use the mi package to impute data, but am running into
problems with the functions it calls.
For instance, I am trying to impute a categorical variable called
"min.func." The mi() function calls the mi.categorical() function to
deal with this variable, which in turn calls the nnet.default()
function, and passes it a fixed parameter MaxNWts=1500. However, as
you can see below, the min.func variable needs a higher threshold than
1500. Is there a way that I can change the MaxNWts parameter that is
being sent to nnet.default()? I've investigated the mi() and
mi.info() functions and cannot see a way.
Thanks for your help! Error message and system info below:
Beginning Multiple Imputation ( Wed Jul 14 10:25:06 2010 ):
Iteration 1
Imputation 1 : min.func*
Error while imputing variable: min.func , model: mi.categorical
Error in nnet.default(X, Y, w, mask = mask, size = 0, skip = TRUE,
softmax = TRUE, :
too many (2608) weights
System is Mac OS X 10.5.8, R version 2.9.2
Andrew Miles
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