如何计算循环数据的标准偏差

How to calculate standard deviation of circular data

我已按照此处列出的建议计算循环数据的平均值:

https://en.wikipedia.org/wiki/Mean_of_circular_quantities

但我也想计算标准偏差。

#A vector of directional data (separated by 20 degrees each)
Dir2<-c(350,20,40)

#Degrees to Radians
D2R<-0.0174532925

#Radians to Degrees
Rad2<-Dir2 * D2R


Sin2<-sin(Rad2)
SinAvg<-mean(Sin2)

Cos2<-cos(Rad2)
CosAvg<-mean(Cos2)

RADAVG<-atan2(SinAvg, CosAvg)
DirAvg<-RADAVG * R2D

上面给了我平均值,但是我不知道怎么计算SD

我试图只取正弦和余弦的标准偏差的平均值,但我得到了不同的答案。

SinSD<-sd(Sin2)
CosSD<-sd(Cos2)
mean(CosSD, SinSD)

您可以为此使用 circular 软件包:

x <- circular(Rad2)
mean(x)
# Circular Data: 
# Type = angles 
# Units = radians 
# Template = none 
# Modulo = asis 
# Zero = 0 
# Rotation = counter 
# [1] 0.2928188 # The same as yours
sd(x)
# [1] 0.3615802

手动,

sqrt(-2 * log(sqrt(sum(Sin2)^2 + sum(Cos2)^2) / length(Rad2)))
# [1] 0.3615802

sd.circular.

的源码可以看出

另见 here and here