Directional (version 4.7)

Uniformity test for circular data: Uniformity tests for circular data.

Description

Hypothesis tests of uniformity for circular data.

Usage

kuiper(u, rads = FALSE, R = 1)
watson(u, rads = FALSE, R = 1)

Arguments

u

A numeric vector containing the circular data, which cna be expressed in degrees or radians.

rads

A boolean variable. If the data are in radians, put this TRUE. If the data are expressed in degrees make this FALSE.

R

If R = 1the asymtptotic p-value will be calcualted. If R is greater than 1 the bootstrap p-value is returned.

Value

A vector including:

Test

The value of the test statistic.

p-value

The p-value of the test (bootstrap or asymptotic depends upon the value of the argument R).

Details

The high concentration (hcf.circaov), log-likelihood ratio (lr.circaov), embedding approach (embed.circaov) or the non equal concentration parameters approach (het.circaov) is used.

References

Jammalamadaka, S. Rao and SenGupta, A. (2001). Topics in Circular Statistics, pg. 153-55 (Kuiper's test) & 156-157 (Watson's test).

See Also

rayleigh, vmf.mle, rvonmises

Examples

# NOT RUN {
x <- rvonmises(n = 40, m = 2, k = 10)
kuiper(x, rads = TRUE)
watson(x, rads = TRUE)
x <- rvonmises(40, m = 2, k = 0)
kuiper(x, rads = TRUE)
watson(x, rads = TRUE)
# }