I get the following error when attempting to impute missing data in the
attached dataset:
1 Error in eigen(thetanew[2:nrow(thetanew), 2:ncol(thetanew)], only.values
> = TRUE, :
infinite or missing values in 'x'
A summary of the data set reveals no column with entirely missing or
constant values, and if I reduce the tolerance greatly, the problem goes
away.
I receive the following error when running amelia on a dataset with high
missingness:
Error in if (diff > iter.hist[count, 1] && count > 2) { :
missing value where TRUE/FALSE needed
This error has popped up several times, in different imputations (I'm
trying for five) and at different points of the EM chain. I can't get
through five imputations without this crash. What does the error mean?
Here is my code:
output <- amelia(data_1, cs = "country", ts = "year", intercs = TRUE,
polytime = 2, p2s = 2, logs = c("gdpPPP2005", "gdppcppp", "pop",
"gnipc"), ords = c("inc_group", "polxcons", "bnkv137", "bnkv114",
"iaeexbgt"), noms = c("region", "legor"), empri = 0.01*nrow(data_1))
thanks,
Amanda Pinkston
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