vm.bootstrap.ci: Bootstrap Confidence Intervals

Description

Generates simple bootstrap confidence intervals for the parameters of a von Mises distribtution: the mean direction mu, and the concentration parameter kappa.

Usage

vm.bootstrap.ci(x, bias=FALSE, alpha=0.05, reps=1000, print=TRUE)

Value

A list is returned with the following components: mu.ci and kappa.ci contain the limits of the confidence intervals for mu and kappa respectively. mu.reps and kappa.reps contain the estimates of mu and kappa for each resampled data set.

Arguments

x: vector of angular measurements in radians.
bias: logical flag: if TRUE, the replication estimates for kappa are computed with a bias corrected method. See est.kappa. Default is FALSE, i.e. no bias correction.
alpha: parameter determining level of confidence intervals. 1-alpha confidence intervals for mu and kappa are computed. By default, 95% confidence intervals are generated.
reps: number of resampled data sets to use. Default is 1000.
print: logical flag indicating whether the algorithm should print a message indicating which set of replicates is currently being drawn. Default is TRUE.

Details

Percentile confidence intervals are computed by resampling from the original data set B times. For each resampled data set, the MLE's of mu and kappa are computed. The bootstrap confidence intervals are the alpha/2 and 1-alpha/2 percentiles of the B MLE's computed for each resampled data set.

Examples

Run this code

x <- rvm(25, 0, 3)
x.bs <- vm.bootstrap.ci(x, alpha=.10)
hist(x.bs$kappa.reps)