hcfboot: Bootstrap ANOVA for (hyper-)spherical data

In Directional: A Collection of Functions for Directional Data Analysis

Bootstrap ANOVA for (hyper-)spherical data

Description

Bootstrap ANOVA for (hyper-)spherical data.

Usage

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

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.

Details

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

Value

This is an "htest"class object. Thus it returns a list including:

statistic	The test statistic value.
parameter	The degrees of freedom of the test. Since these are bootstrap based tests this is "NA".
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.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail].

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)

Directional documentation built on Oct. 12, 2023, 1:07 a.m.