Uniformity tests for circular data.
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 = 1the asymtptotic 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.
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). |
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) & 156-157 (Watson's test).
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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