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The null hypothesis is whether an IAG distribution fits the data well, where the altenrative is that ESAG distribution is more suitable.
iagesag(x, B = 1, tol = 1e-07)This is an "htest"class object. Thus it returns a list including:
The test statistic value.
The degrees of freedom of the test. If bootstrap was employed this is "NA".
The p-value of the test.
A character with the alternative hypothesis.
A character with the test used.
A character vector with two elements.
A numeric matrix with three columns containing the data as unit vectors in Euclidean coordinates.
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.
The tolerance to accept that the Newton-Raphson algorithm used in the IAG distribution has converged.
Michail Tsagris.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.
Essentially it is a test of rotational symmetry, whether the two
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.
fishkent, iagesag, pc.test, esag.mle, kent.mle,
x <- rvmf(100, rnorm(3), 15)
iagesag(x)
fishkent(x, B = 1)
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