Quantile-Quantile Linearised Plot for Circular Distributions
Quantile-Quantile Linearised Plot for Circular Distributions
Uniformly distributed orientations should yield a straight line through the origin. Systematic departures from linearity will indicate preferred orientation.
circular_qqplot( x, axial =TRUE, xlab = paste("i/(n+1)"), ylab =NULL, main ="Circular Quantile-Quantile Plot", add_line =TRUE, col ="#B63679FF",...)
Arguments
x: numeric. Angles in degrees
axial: Logical. Whether data are uniaxial (axial=FALSE)
xlab, ylab, main: plot labels.
add_line: logical. Whether to connect the points by straight lines?
col: color for the dots.
...: graphical parameters
Returns
plot
Examples
# von Mises distributionx_vm <- rvm(100, mean =0, kappa =2)circular_qqplot(x_vm, pch =20)x_norm <- rnorm(100, mean =0, sd =25)circular_qqplot(x_norm, pch =20)# uniform (random) datax_unif <- runif(100,0,360)circular_qqplot(x_unif, pch =20)
References
Borradaile, G. J. (2003). Statistics of earth science data: their distribution in time, space, and orientation (Vol. 351, p. 329). Berlin: Springer.