Publication Type
Conference Paper
Version
submittedVersion
Publication Date
12-2003
Abstract
The mixed inverse Gaussian given by Whitmore (Scand. J. Statist., 13, 1986, 211–220) provides a convenient way for testing the goodness-of-fit of a pure inverse Gaussian distribution. The test is a one-sided score test with the null hypothesis being the pure inverse Gaussian (i.e. the mixing parameter is zero) and the alternative a mixture. We devise a simple score test and study its finite sample properties. Monte Carlo results show that it compares favourably with the smooth test of Ducharme (Test, 10, 2001, 271-290). In practical applications, when the pure inverse Gaussian distribution is rejected, one is interested in making inference about the general values of the mixing parameter. However, as it is well known that the inverse Gaussian mixture is a defective distribution; hence, the standard likelihood inference cannot be applied. We propose several alternatives and provide score tests for the mixing parameter. Finite sample properties of these tests are examined by Monte Carlo simulation. Copyright © 2010 John Wiley & Sons, Ltd.
Keywords
defective distribution; inverse gaussian; score tests
Discipline
Econometrics
Research Areas
Econometrics
Publication
Bernoulli Society East Asian and Pacific Regional (EAPR) Conference 2003
Citation
YANG, Zhenlin.
Score Tests for Inverse Gaussian Mixture. (2003). Bernoulli Society East Asian and Pacific Regional (EAPR) Conference 2003.
Available at: https://ink.library.smu.edu.sg/soe_research/1041
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.