Error in R (mice package), too many weights
r, r-mice
Solution
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)`
Problem
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?