Generalized inferences on the means and scales of two independent Inverse Gaussian populations
碩士 === 國立交通大學 === 統計學研究所 === 94 === The IG distribution has gotten intensive attentions in statistical application fields by reason of it is an ideal candidate for modeling positive, right-skewed data. The classical procedures have difficulties in analysis non-homogeneous IG data. Hence, the exact i...
| Main Authors: | , |
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| Format: | Others |
| Language: | en_US |
| Published: |
2006
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| Online Access: | http://ndltd.ncl.edu.tw/handle/75509882743669748836 |
| Summary: | 碩士 === 國立交通大學 === 統計學研究所 === 94 === The IG distribution has gotten intensive attentions in statistical application fields by reason of it is an ideal candidate for modeling positive, right-skewed data. The classical procedures have difficulties in analysis non-homogeneous IG data. Hence, the exact inferences on making inferences for two IG means and scales deserve further research. In this thesis, we present a convenient approach based on the generalized p-value and generalized confidence methods to perform the hypothesis testing and confidence intervals for mean and scale of one IG population as well as the ratio of means and scales of two independent IG populations. Illustrative examples show that the confidence lengths obtained by the generalized methods are the smallest or close to the smallest length. Furthermore, the simulation studies show that our coverage probabilities and type I error are very close to the nominal levels.
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