Directional (version 6.8)

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)

Value

This is an "htest"class object. Thus it returns a list including:

statistic

The test statistic value.

parameter

This is usually the degrees of freedom of the test, but here this is "NA" because the asymptotic based p-value is computed in a different way or because bootstrap was employed.

p.value

The p-value of the test.

alternative

A character with the alternative hypothesis.

method

A character with the test used.

data.name

A character vector with two elements.

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

Author

Michail Tsagris.

R implementation and documentation: Michail Tsagris and Giorgos Athineou <[e-mail]>.

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) and pg. 156--157 (Watson's test).

See Also

rayleigh, ptest, vmf.mle, rvonmises

Examples

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)