Given a dataset of months, how do I calculate the "average" month, taking into account that months are circular?
months = c(1,1,1,2,3,5,7,9,11,12,12,12)
mean(months)
## [1] 6.333333
In this dummy example, the mean should be in January or December. I see that there are packages for circular statistics, but I'm not sure whether they suit my needs here.
I think
months <- c(1,1,1,2,3,5,7,9,11,12,12,12)
library("CircStats")
conv <- 2*pi/12 ## months -> radians
Now convert from months to radians, compute the circular mean, and convert back to months. I'm subtracting 1 here assuming that January is at "0 radians"/12 o'clock ...
(res1 <- circ.mean(conv*(months-1))/conv)
The result is -0.3457. You might want:
(res1 + 12) %% 12
which gives 11.65, i.e. partway through December (since we are still on the 0=January, 11=December scale)
I think this is right but haven't checked it too carefully.
For what it's worth, the CircStats::circ.mean
function is very simple -- it might not be worth the overhead of loading the package if this is all you need:
function (x)
{
sinr <- sum(sin(x))
cosr <- sum(cos(x))
circmean <- atan2(sinr, cosr)
circmean
}
Incorporating @A.Webb's clever alternative from the comments:
m <- mean(exp(conv*(months-1)*1i))
12+Arg(m)/conv%%12 ## 'direction', i.e. average month
Mod(m) ## 'intensity'