[R] error in NORM lib

[Prof Brian Ripley]

You really need to send such issues to the _package_ maintainer: please 
see the posting guide.  He will need a completely reproducible example.

On Wed, 9 Nov 2005, Leo Gürtler wrote:

> Dear alltogether,
>
> I experience very strange behavior of imputation of NA's with the NORM
> library. I use R 2.2.0, win32.
> The code is below and the same dataset was also tried with MICE and
> aregImpute() from HMISC _without_ any problem.
> The problem is as follows:
>
> (1) using the whole dataset results in very strange imputations - values
> far beyond the maximum of the respective column, > 200%! and this is
> reproducible and true for the whole set of imputed NAs
> (2) using just part (i.e. columns) of the dataset results in the fact
> that some NAs are not imputed at all, i.e. NAs are still in the dataset
> - but there is neither a warning nor an error
> (3) data.augmentation with da.norm() fails, but not after the first
> step, mostly 3-5 steps are ok, then it stops (see below)
>
> The dataset is from educational research and should be almost normal
> distributed (slight deviations, but not really that heavy to explain the
> strange results).
> I don't understand this, because the dataset works well with MICE and
> aregImpute() and other statistics _and_ I checked the manpages and it
> does not seem that the calls are wrong.
> Thus, either it depends on the dataset (but why?) or it is maybe a bug.
>
> I appreciate every help,
>
> thanks,
>
> leo gürtler
>
> <---snip--->
>
> library(norm)
> rngseed(1234)
> load(url("http://www.anicca-vijja.de/lg/dframe.Rdata"))   # load object
> "dframe"
> dim(dframe)
> apply(dframe,2,function(x) sum(is.na(x))) # check how many NAs in the
> dataset
> #dframe <-
> subset(dframe,select=-c(alter,grpzugeh,is1,is4,is6,klassenstufe,mmit,vorai,vorap,voras,vorkf,vorsg,vorvb))
> s1 <- prelim.norm(dframe)
> s1$nmis   # re-check of NAs should be identical to above
> s2 <- prelim.norm(dframe[,1:32])# see below -> still NAs are available -
> _not_ imputed
> thetahat1 <- em.norm(s1)
> theta1 <- da.norm(s1,thetahat1,steps=20,showits=TRUE)  # error:
>                                                       # Steps of Data
> Augmentation:
>                                                       #
> 1...2...3...4...5...6...7...8...Fehler: NA/NaN/Inf in externem
> Funktionsaufruf (arg 2)
> thetahat2 <- em.norm(s2)
> ( imputed1 <- imp.norm(s1,thetahat1,dframe) )    # very strange imputed
> values
>                                                 # almost >200% to big
> than expected
> ( imputed1.1 <- imp.norm(s1,theta1,dframe)  )    # not possible -
> because da.norm gives no result!
> ( imputed2 <- imp.norm(s2,thetahat2,dframe) )    # still NAs in the matrix
>
> # visualize the strange values
> par(mfrow=c(2,1))
> hist(dframe,prob=TRUE)      # histogramm data set with NAs - original values
> lines(density(na.omit(dframe)))
> hist(imputed1,prob=TRUE)   # histogramm of dataset with imputed values
> lines(density(imputed1))
>
>
> </---snip--->
>
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-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595