Score tests for inverse Gaussian mixtures
β Scribed by A. F. Desmond; Z. L. Yang
- Publisher
- John Wiley and Sons
- Year
- 2010
- Tongue
- English
- Weight
- 259 KB
- Volume
- 27
- Category
- Article
- ISSN
- 1524-1904
- DOI
- 10.1002/asmb.876
No coin nor oath required. For personal study only.
β¦ Synopsis
The mixed inverse Gaussian given by Whitmore (biScand. J. Statist., 13, 1986, 211β220) provides a convenient way for testing the goodnessβofβfit of a pure inverse Gaussian distribution. The test is a oneβsided 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, 271β290).
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 Β© 2010 John Wiley & Sons, Ltd.
π SIMILAR VOLUMES
I create a general model to perform score tests on interval censored data. Special cases of this model are the score tests of Finkelstein, Sun and Fay. Although Sun's was derived as a test for discrete data and Finkelstein's and Fay's tests were derived under a grouped continuous model, by writing a
Two methods of setting confidence intervals for test scores and testing the significance of test score differences are compared with respect to their simplicity and the similarity of their results. The conventional method, which is based on obtained scores, is unquestionably simpler than the technic