Permutation based 2-sample mean test for (hyper-)spherical data: Permutation based 2-sample mean test for (hyper-)spherical data
Description
Permutation based 2-sample mean test for (hyper-)spherical data.
Usage
hcf.perm(x1, x2, B = 999)
lr.perm(x1, x2, B = 999)
hclr.perm(x1, x2, B = 999)
embed.perm(x1, x2, B = 999)
het.perm(x1, x2, B = 999)
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 permutation 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.
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.
B
The number of permutations to perform.
Author
Michail Tsagris.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.
Details
The high concentration (hcf.perm), log-likelihood ratio (lr.perm), high concentration
log-likelihood ratio (hclr.perm), embedding approach (embed.perm) or the non equal
concentration parameters approach (het.perm) 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. (2024). An investigation of hypothesis testing procedures for circular
and spherical mean vectors. Communications in Statistics-Simulation and Computation, 53(3): 1387--1408.