Directional (version 6.1)

Anova for circular data: Analysis of variance for circular data

Description

Analysis of variance for circular data.

Usage

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)

Value

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.

Arguments

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.

Author

Michail Tsagris.

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

Details

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.

References

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.

Tsagris M. and Alenazi A. (2022). An investigation of hypothesis testing procedures for circular and spherical mean vectors. Communications in Statistics-Simulation and Computation (Accepted for publication).

See Also

hclr.aov, hcfcirc.boot, hcfcircboot

Examples

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)