Bootstrapped Estimates for Circular Dispersion

Calculates bootstrapped estimates of the circular dispersion, its standard error and its confidence interval.

Usage

circular_dispersion_boot(
  x,
  y = NULL,
  w = NULL,
  w.y = NULL,
  R = 1000,
  conf.level = 0.95,
  ...
)

Arguments

x, y

vectors of numeric values in degrees. length(y) is either 1 or length(x)

w, w.y

(optional) Weights. A vector of positive numbers and of the same length as x. w.y is the (optional) weight of y.

R

positive integer. The number of bootstrap replicates (1000 by default).

conf.level

Level of confidence: \((1 - \alpha \%)/100\). (0.95 by default).

...

optional arguments passed to boot::boot()

Value

list containing:

MLE

the maximum likelihood estimate of the circular dispersion

sde

standard error of MLE

CI

lower and upper limit of the confidence interval of MLE

See also

circular_dispersion()

Examples

data("nuvel1")
PoR <- subset(nuvel1, nuvel1$plate.rot == "na")
sa.por <- PoR_shmax(san_andreas, PoR, "right")
circular_dispersion(sa.por$azi.PoR, y = 135, w = weighting(san_andreas$unc))
#> [1] 0.1384805
circular_dispersion_boot(sa.por$azi.PoR, y = 135, w = weighting(san_andreas$unc), R = 1000)
#> $MLE
#> [1] 0.2610566
#> 
#> $sde
#> [1] 0.01132889
#> 
#> $CI
#> [1] 0.2375632 0.2833176
#>