Directional (version 6.1)

Bootstrap ANOVA for (hyper-)spherical data: Bootstrap ANOVA for (hyper-)spherical data

Description

Bootstrap ANOVA for (hyper-)spherical data.

Usage

hcfboot(x, ina, B = 999)
hetboot(x, ina, B = 999)

Value

A vector including two or three numbers, the test statistic value, the bootstrap p-value of the test and the common concentration parameter kappa based on all the data.

Arguments

x

A matrix with the combined data (from all groups) in Euclidean coordinates, i.e. unit vectors.

ina

The grouping variables. A factor or a numerical vector specifying the groups to which each observation belongs to.

B

The number of bootstraps to perform.

Author

Michail Tsagris.

R implementation and documentation: Michail Tsagris .

Details

The high concentration (hcfboot), or the non equal concentration parameters approach (hetboot) 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

hcf.boot, hcf.aov

Examples

x <- rvmf(60, rnorm(3), 10)
ina <- rep(1:3, each = 20)
hcfboot(x, ina)