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The data set that I
am looking at consists of thousands of n.samples-by-p.variables
multivariate data sets containing missing data. For each data set I
would like to impute missing data using DA method, so I've decided to explore
and use a loop. Unfortunately, I am having not much of a success with
DA within a large 'for' loop. I am having convergence problem for the starting values
(created by either bootstrap or parallel chains) at some point within the
loop. I have checked that it wasn't the case when I manually run DA
on the data sets which caused the non-convergence. I wonder whether I
shouldn't use DA within a loop at all or is there something else I should be
made aware off. Has anyone came across with a similar problem
before? Any recommendations would be great.
Thanks in
advance.
Ken
Nip
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