test.AD {gofIG}R Documentation

The Anderson-Darling goodness-of-fit test for the inverse Gaussian family

Description

This function computes the goodness-of-fit test for the inverse Gaussian family in the spirit of Anderson and Darling. Note that this tests the composite hypothesis of fit to the family of inverse Gaussian distributions, i.e. a bootstrap procedure is implemented to perform the test.

Usage

test.AD(data, B = 500)

Arguments

data

a vector of positive numbers.

B

number of bootstrap iterations used to obtain p value.

Details

The Anderson-Darling test is computed as described in Allison et. al. (2019). The p value is obtained by a parametric bootstrap procedure.

Value

a list containing the value of the name of the test statistic, the value of the test statistic, the bootstrap p value, the values of the estimators, and the number of bootstrap iterations:

$Test

the name of the used test statistic.

$T.value

the value of the test statistic.

$p.value

the approximated p value.

$par.est

the estimated parameters.

$boot.run

number of bootstrap iterations.

References

Allison, J.S., Betsch, S., Ebner, B., Visagie, I.J.H. (2019) "New weighted L^2-type tests for the inverse Gaussian distribution", arXiv:1910.14119. LINK

Examples

test.AD(rmutil::rinvgauss(20,2,1),B=100)


[Package gofIG version 1.0 Index]