Hi, a question about the circular mean function in the package
CircStats:
Can anyone shed some light on why the circ mean function seems to make
sense for the first 2 set of bearings and then the mean of 225 and 45
degrees gives an unexpected 180 deg.
> deg(circ.mean(c(rad(222),rad(45))))%%360
[1] 133.5
> deg(circ.mean(c(rad(224),rad(45))))%%360
[1] 134.5
> deg(circ.mean(c(rad(225),rad(45))))%%360
[1] 180
> deg(circ.mean(c(rad(226),rad(45))))%%360
[1] 315.5
Can anyone explain this???
This problem was first detected when I was trying to take the circ
weighted means of my data:
With 2 groups of bearings:
x <- c(270,180)
y <- c(45,270)
the circular mean of these bearings gives:
> deg(circ.mean(c(rad(x),rad(y))))%%360
[1] 257.2356
When finding the weighted means I get this:
> meany <- circ.mean(rad(y))
> meanx <- circ.mean(rad(x))
> deg(circ.weighted.mean(c(meanx,meany),c(2,2)))%%360
[1] 281.25
The function for weighted mean I am using:
circ.weighted.mean <- function (x,w)
{
sinr <- sum(w*sin(x))
cosr <- sum(w*cos(x))
circmean <- atan(sinr, cosr)
circmean
}
I am assuming that the problem that mention above is the cause of the
different mean bearings.
Am I missing something fundamental here?
Thanks,
Mike
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