test.HK1 {gofIG} | R Documentation |
This function computes the goodness-of-fit test for the inverse Gaussian family due to Henze and Klar (2002).
test.HK1(data, a = 0, B = 500)
data |
a vector of positive numbers. |
a |
positive tuning parameter. |
B |
number of bootstrap iterations used to obtain p value. |
The test statistics is a weighted integral over the squared modulus of some measure of deviation of the empirical distribution of given data from the family of inverse Gaussian laws, expressed by means of the empirical Laplace transform.
a list containing the value of the name of the test statistic, the used tuning parameter, the parameter estimation method, 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.
$parameter
the value of the tuning parameter.
$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.
Henze, N. and Klar, B. (2002) "Goodness-of-fit tests for the inverse Gaussian distribution based on the empirical Laplace transform", Annals of the Institute of Statistical Mathematics, 54(2):425-444. doi:10.1023/A:1022442506681
test.HK1(rmutil::rinvgauss(20,2,1),B=100)