
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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