# kuiper: Uniformity tests for circular data. In Directional: A Collection of Functions for Directional Data Analysis

## Description

Hypothesis tests of uniformity for circular data.

## Usage

 ```1 2 3``` ```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.

## 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.

## 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).

## Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris mtsagris@uoc.gr and Giorgos Athineou <gioathineou@gmail.com>.

## References

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

```rayleigh, vmf.mle, rvonmises ```
 ```1 2 3 4 5 6``` ```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) ```