Analysis of variance for circular data
Analysis of variance for circular data.
hcf.circaov(u, ina, rads = FALSE) hclr.circaov(u, ina, rads = FALSE) lr.circaov(u, ina, rads = FALSE) het.circaov(u, ina, rads = FALSE) embed.circaov(u, ina, rads = FALSE)
u |
A numeric vector containing the data. |
ina |
A numerical or factor variable indicating the group of each value. |
rads |
If the data are in radians, this should be TRUE and FALSE otherwise. |
The high concentration (hcf.circaov), high concentration likelihood ratio (hclr.aov), 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. |
kappa |
The concentration parameter based on all the data. If the het.circaov is used this argument is not returned. |
Michail Tsagris.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr and Giorgos Athineou <gioathineou@gmail.com>.
Mardia, K. V. and Jupp, P. E. (2000). Directional statistics. Chicester: John Wiley & Sons.
Rumcheva P. and Presnell B. (2017). An improved test of equality of mean directions for the Langevin-von Mises-Fisher distribution. Australian & New Zealand Journal of Statistics, 59(1), 119-135.
x <- rvonmises(100, 2.4, 15) ina <- rep(1:4,each = 25) hcf.circaov(x, ina, rads = TRUE) lr.circaov(x, ina, rads = TRUE) het.circaov(x, ina, rads = TRUE) embed.circaov(x, ina, rads = TRUE)
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