# 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 R Documentation

## 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 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.

fishkent, iagesag, pc.test, esag.mle, kent.mle, 
x <- rvmf(100, rnorm(3), 15)