Error in R (mice package), too many weights

Question

I get the following error while imputing missing cases with the mice function from the library "mice"

 Error in nnet.default(X, Y, w, mask = mask, size = 0, skip = TRUE, softmax = TRUE,  :
too many (1104) weights

The problem is generated by the function mice.impute.polr and mice.impute.polyreg because of the default maximum number of weights. I can not solved it by using the command substitute and neither by copying the functions' code and writing the new functions mice.impute.polr and mice.impute.polyreg (because of a function I cannot find call augment). I've told that I should go to the source code to modify it.

How can I do it? Are there any other solution?

score 10 · Accepted Answer · answered Apr 20 '15 at 10:35

The neural net function called by mice() is stopping because the "maximum allowable number of weights" has been exceeded. The MaxNWts argument to nnet is there to prevent running code that will take a very long time to complete.

If you don't mind waiting then you can increase the MaxNWts parameter by passing it directly to mice(), which will be picked up by nnet():

mice(data = df_with_nas, MaxNWts = 2000)

score 5 · Answer 2 · answered Jun 21 '17 at 01:34

5

Increase the MaxNWts in mice through nnet.MaxNWts argument

mice(data = df_with_nas, nnet.MaxNWts = 2000)

This is described in the documentation of the mice imputation functions, e.g. mice.impute.polr

answered Jun 21 '17 at 01:34

Gordon Li

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score -1 · Answer 3 · answered Apr 04 '17 at 02:07

-1

I had the same problem. I found one factor variable has more than 10 levels. After I delete this var, the error is gone.

answered Apr 04 '17 at 02:07

CcMango

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Error in R (mice package), too many weights

3 Answers3