Hi all,
I need to replace missing values in a matrix by 10 % of the lowest available
value in the matrix. I've got a function I've used earlier to replace negative
values by the lowest value, in a data frame, but I'm not sure how to modify
it...
nonNeg = as.data.frame(apply(orig.df, 2, function(col) # Change negative values
to a small value, close to zero
{
min.val = min(col[col > 0])
col[col < 0] = (min.val / 10)
col # Column index
}))
I think this is how to start, but the NA replacement part doesn't work...
newMatrix = as.matrix(apply(oldMatrix, 2, function(col)
{
min.val = min(mData, na.rm = T) # Find the smallest value in the dataset
col[col == NA] = (min.val / 10) # Doesn't work...
col # Column index
}
Does any of you have any suggestions?
Best regards,
Joel
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