I know that IEEE 754 defines NaNs to have the following bitwise representation:
0
or 1
The statistical environment R uses NaN
payloads to distinguish one specific NaN
as representing a statistical "missing value", which prints as NA
. This allows 'missing' to propagate through numeric calculations -- although when combining a missing value with another NaN
it is not predictable which one is propagated.