hcf.boot: Bootstrap 2-sample mean test for (hyper-)spherical data In Directional: A Collection of Functions for Directional Data Analysis

Description

Bootstrap 2-sample mean test for (hyper-)spherical data.

Usage

 ```1 2 3 4 5``` ```hcf.boot(x1, x2, fc = TRUE, B = 999) lr.boot(x1, x2, B = 999) hclr.boot(x1, x2, B = 999) embed.boot(x1, x2, B = 999) het.boot(x1, x2, B = 999) ```

Arguments

 `x1` A matrix with the data in Euclidean coordinates, i.e. unit vectors. `x2` A matrix with the data in Euclidean coordinates, i.e. unit vectors. `fc` A boolean that indicates whether a corrected F test should be used or not. `B` The number of bootstraps to perform.

Details

The high concentration (hcf.boot), log-likelihood ratio (lr.boot), high concentration log-likelihood ratio (hclr.boot), embedding approach (embed.boot) or the non equal concentration parameters approach (het.boot) is used.

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.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.

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.

```hcf.aov, hcf.perm, spherconc.test, conc.test ```
 ```1 2 3 4 5 6 7``` ```x <- rvmf(60, rnorm(3), 15) ina <- rep(1:2, each = 30) x1 <- x[ina == 1, ] x2 <- x[ina == 2, ] hcf.boot(x1, x2) lr.boot(x1, x2) het.boot(x1, x2) ```