iagesag: Hypothesis test for IAG distribution over the ESAG...

In Directional: A Collection of Functions for Directional Data Analysis

Hypothesis test for IAG distribution over the ESAG distribution

Description

The null hypothesis is whether an IAG distribution fits the data well, where the altenrative is that ESAG distribution is more suitable.

Usage

iagesag(x, B = 1, tol = 1e-07)

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 \gamma 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 [e-mail].

References

Paine P.J., Preston S.P., Tsagris M. and Wood A.T.A. (2018). An Elliptically Symmetric Angular Gaussian Distribution. Statistics and Computing, 28(3):689–697.

See Also

fishkent, iagesag, pc.test, esag.mle, kent.mle,

Examples

x <- rvmf(100, rnorm(3), 15)
iagesag(x)
fishkent(x, B = 1)

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