Masking Missing Values
Sometimes the code for a missing value gets quite complex (maybe including "and"
or "or" clauses) and diffiult to manage. Since you hve to specofy exactly the
same values in vectors or matrices you can easily make mistakes. One approach is
to cut-nad-paste the missing value clause into everything, but that's messy.
Here's an example using a mask.
mask <- !is.na(spc.plt) & !is.na(elev)
So, we just create a logical variable called mask (actually y can call it
anything you want) and then use it as a logical subscript in any vector or
matric where we need to eleiminate items where soenthing is missing. If you
have lots of missing values in your data, you can havemultiple masks andname
thenm for what they are missing, e.g.
has.elev <- !is.na(elev)