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

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/iagesag.R

Description

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

Usage

1
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 γ parameters are equal to zero. This works for spherical data only.

Value

A vector including:

test

The value of the test statistic.

p-value or Bootstrap p-value

The p-value of the test.

Author(s)

Michail Tsagris

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

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, esag.mle, kent.mle, iag.mle

Examples

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2
3
x <- rvmf(100, rnorm(3), 15)
iagesag(x)
fishkent(x, B = 1)

Directional documentation built on Nov. 8, 2021, 1:07 a.m.