I can't quite figure out what the cor() function does with the different
na.methods "omit" and "available". I find that each of these methods
yields a different answer, even if there is no missing data.
example:
> rn1 <- rnorm(3)
> rn1
[1] 0.52170 -0.34945 0.76141
> rn2 <- rnorm(3)
> rn2
[1] 0.44834 -2.10544 -0.91762
> cor(rn1, rn2)
[1] 0.71767
> cor(rn1, rn2, na.method = "omit")
[1] 0.71767
Which is exactly what I'd expect. But when
> cor(rn1, rn2, na.method = "available")
[1] 0.35884
is the result.
Why is this, when there is no missing data? If there is missing data,
the two methods also yield different answers, though "omit" does what
I'd expect, which is compute the correlation based on whatever pairs are
available. I can't figure out what "available" does. Any insight will be
deeply appreciated
Kim Elmore
--
Kim Elmore, OU/CIMMS/NSSL
"All of weather is divided into three parts:
Yes, No and Maybe. The greatest of these is Maybe."
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