I figured this one out. I'm sending the solution back to the help
list so that there is a record of how to deal with this problem, since
it does not seem to be documented elsewhere.
The mi.info object that you pass to the the mi() function contains a
value called "params" which allows you to set the parameters used in
each imputation model. If you access it like so
info=mi.info(impute.data)
info[["min.func"]]$params
you are presented with a matrix showing a value for only two
parameters that are passed to every model, n.iter and draw.from.beta.
You can add any other parameters that you want like so:
info[["min.func"]]$params$MaxNWts=3000
This will add the parameter MaxNWts to the min.func model. This seems
to have solved the problem I outlined below.
Andrew Miles
On Jul 14, 2010, at 10:33 AM, Andrew Miles wrote:
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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