vm.bootstrap.ci {CircStats}

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)

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.

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.

Note

The confidence intervals are printed to the screen.

See Also

vm.ml, est.kappa

Examples

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