Uniformity test for circular data | R Documentation |

Hypothesis tests of uniformity for circular data.

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

`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. |

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.

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. |

Michail Tsagris.

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

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

```
rayleigh, ptest, vmf.mle, rvonmises
```

```
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)
```

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