Publication Type
Journal Article
Version
acceptedVersion
Publication Date
12-2011
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.
Keywords
defective distribution, inverse gaussian, score tests
Discipline
Econometrics
Research Areas
Econometrics
Publication
Applied Stochastic Models in Business and Industry
Volume
27
Issue
6
First Page
633
Last Page
648
ISSN
1524-1904
Identifier
10.1002/asmb.876
Publisher
Wiley
Citation
Desmond, A. F. and YANG, Zhenlin.
Score Tests for Inverse Gaussian Mixtures. (2011). Applied Stochastic Models in Business and Industry. 27, (6), 633-648.
Available at: https://ink.library.smu.edu.sg/soe_research/524
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1002/asmb.876