| Hypothesis test for SIPC distribution over the SESPC distribution {Directional} | R Documentation |
Hypothesis test for SIPC distribution over the SESPC distribution
Description
The null hypothesis is whether an SIPC distribution fits the data well, where the altenrative is that SESPC distribution is more suitable.
Usage
pc.test(x, B = 1, tol = 1e-06)
Arguments
x |
A numeric matrix with three columns containing the data as unit vectors in Euclidean coordinates. |
B |
The number of bootstrap re-samples. By default is set to 999. If it is equal to 1, no bootstrap is performed and the p-value is obtained throught the asymptotic distribution. |
tol |
The tolerance to accept that the Newton-Raphson algorithm used in the IAG distribution has converged. |
Details
Essentially it is a test of rotational symmetry, whether the two \theta parameters are equal to zero. This works for spherical data only.
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. If bootstrap was employed 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 mtsagris@uoc.gr.
References
Tsagris M. and Alzeley O. (2023). Circular and spherical projected Cauchy distributions: A Novel Framework for Circular and Directional Data Modeling. https://arxiv.org/pdf/2302.02468.pdf
See Also
Examples
x <- rvmf(100, rnorm(3), 15)
iagesag(x)
pc.test(x)