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.

Usage

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

Value

plot

References

Borradaile, G. J. (2003). Statistics of earth science data: their distribution in time, space, and orientation (Vol. 351, p. 329). Berlin: Springer.

See also

cunif()

Other circ-qqplot: vm_qqplot()

Examples

set.seed(20250411)

# von Mises distribution
x_vm <- rvm(100, mean = 0, kappa = 2)
circular_qqplot(x_vm, pch = 20)


x_wcauchy <- rwcauchy(100, mean = 0, rho = 0.5)
circular_qqplot(x_wcauchy, pch = 20)


# circular uniform data
x_cunif <- rcunif(100)
circular_qqplot(x_cunif, pch = 20)