Inferences on the common mean of several inverse Gaussian populations
This paper presents procedures for hypothesis testing and interval estimation for the common mean of several inverse Gaussian populations when the scalar parameters are unknown and unequal. The proposed approaches are hybrids between the generalized inference method and the large-sample theory. Some...
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Veröffentlicht in: | Computational statistics & data analysis 2010-04, Vol.54 (4), p.906-915 |
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Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | This paper presents procedures for hypothesis testing and interval estimation for the common mean of several inverse Gaussian populations when the scalar parameters are unknown and unequal. The proposed approaches are hybrids between the generalized inference method and the large-sample theory. Some simulation results are presented to compare the performance of the proposed approaches with that of the existing approach. The simulation results indicate that one of the proposed approaches performs better than the existing approach in most cases. Furthermore, our approaches can be simply carried out by a few simulation steps. Finally, the proposed approaches are illustrated by using three examples. |
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ISSN: | 0167-9473 1872-7352 |
DOI: | 10.1016/j.csda.2009.09.039 |