Score Tests for Inverse Gaussian Mixture
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 paramet...
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sg-smu-ink.soe_research-20402018-06-01T04:32:06Z Score Tests for Inverse Gaussian Mixture YANG, Zhenlin 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. 2003-12-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/1041 https://ink.library.smu.edu.sg/context/soe_research/article/2040/viewcontent/Score_Tests_for_Inverse_Gaussian_Mixtures.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University defective distribution; inverse gaussian; score tests Econometrics |
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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. |
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YANG, Zhenlin |
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YANG, Zhenlin |
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YANG, Zhenlin |
title |
Score Tests for Inverse Gaussian Mixture |
title_short |
Score Tests for Inverse Gaussian Mixture |
title_full |
Score Tests for Inverse Gaussian Mixture |
title_fullStr |
Score Tests for Inverse Gaussian Mixture |
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Score Tests for Inverse Gaussian Mixture |
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score tests for inverse gaussian mixture |
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Institutional Knowledge at Singapore Management University |
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2003 |
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https://ink.library.smu.edu.sg/soe_research/1041 https://ink.library.smu.edu.sg/context/soe_research/article/2040/viewcontent/Score_Tests_for_Inverse_Gaussian_Mixtures.pdf |
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