Hello - I am using the MICE package to impute missing values - the input data are up to six vectors of parallel hourly temperature measurements for Scottish weather stations across a calendar year. None of the vectors have more than 5% NAs as I have filtered ones with more out. Most of the sets work fine with MICE but with a few I get an error message:
This data set, which generated the error message has five columns iter imp variable 1 1 986Error in terms.formula(tmp, simplify = TRUE) : invalid term in model formula 986 is the station number which is the column name here for the first column. The third to fifth columns don't have any NAs and the first and second have fewer than 1% - but they do have the NAs concentrated as strings of 20 or so near the beginning of the data set. I am puzzled as to why certain datasets, which don't seem very different from the others provoke the error message - the only thing which I am wondering is whether MICE has a problem with a too large concentration of the NAs in particular regions but I can't find any reference to this in the literature. Has anyone else come across this as a problem, and if so, what did they do about it? Thanks Nick Wray [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.