circular_sd_error function

Standard Error of Mean Direction of Circular Data

Measure of the chance variation expected from sample to sample in estimates of the mean direction. It is a parametric estimate of the the circular standard error of the mean direction by the particular form of the standard error for the von Mises distribution. The approximated standard error of the mean direction is computed by the mean resultant length and the MLE concentration parameter $\kappa$.

circular_sd_error(x, w = NULL, axial = TRUE, na.rm = TRUE)

Arguments

• x: numeric vector. Values in degrees.

• w: (optional) Weights. A vector of positive numbers and of the same length as x.

• axial: logical. Whether the data are axial, i.e. pi-periodical (TRUE, the default) or directional, i.e. $2 \pi$-periodical (FALSE).

• na.rm: logical value indicating whether NA values in x

  should be stripped before the computation proceeds.

Returns

numeric

Examples

# Example data from Davis (1986), pp. 316
finland_stria <- c(
  23, 27, 53, 58, 64, 83, 85, 88, 93, 99, 100, 105, 113,
  113, 114, 117, 121, 123, 125, 126, 126, 126, 127, 127, 128, 128, 129, 132,
  132, 132, 134, 135, 137, 144, 145, 145, 146, 153, 155, 155, 155, 157, 163,
  165, 171, 172, 179, 181, 186, 190, 212
)
circular_sd_error(finland_stria, axial = FALSE)

data(san_andreas)
data("nuvel1")
PoR <- subset(nuvel1, nuvel1$plate.rot == "na")
sa.por <- PoR_shmax(san_andreas, PoR, "right")
circular_sd_error(sa.por$azi.PoR, w = 1 / san_andreas$unc)

References

N.I. Fisher (1993) Statistical Analysis of Circular Data, Cambridge University Press.

Davis (1986) Statistics and data analysis in geology. 2nd ed., John Wiley & Sons.

See Also

mean_resultant_length(), circular_mean()