MCE {CircOutlier} | R Documentation |
Mean circular error
MCE(y,Y,n)
y |
observed values of the response variable are calculated based on model
having a VonMises distribution with circular mean 0 and concentration parameter k. |
Y |
the estimeted value of y under model |
n |
the sample size |
This function may be considered as a type of arithmetic mean which is not robust to the existence of outlier.thus it can be used to detect the possible outliers in the circular regression.
Number, that is mean circular error.
Azade Ghazanfarihesari, Majid Sarmad
A. H. Abuzaid, A. G. Hussin & I. B. Mohamed (2013) Detection of outliers in simple circular regression models using the mean circular error statistics.
circular, CircStats
#Generate a data set dependent of circular variables.
library(CircStats)
n <- 50
x <- rvm(n = 50, 0, 2)
y <- rvm(n = 50, pi/4, 5)
# Fit a circular-circular regression model.
circ.lm <- circ.reg(x, y, order = 1)
Y <- circ.lm$fitted
MCE(y, Y, n)